On the approval of the National Strategy for Large-scale digitalization and total implementation of artificial intelligence technologies "Digital Qazaqstan" until 2029

Decree of the President of the Republic of Kazakhstan dated June 9, 2026 No. 1311.

 In accordance with paragraph 3 of the National Action Plan for the implementation of the Address of the Head of State to the People of Kazakhstan dated September 8, 2025 "Kazakhstan in the era of artificial intelligence: current challenges and their solutions through digital transformation", approved by Decree of the President of the Republic of Kazakhstan dated October 13, 2025 No. 1042, I DECREE:

     1. To approve the attached National Strategy for Large-scale Digitalization and Total Implementation of artificial intelligence Technologies "Digital Qazaqstan" until 2029 (hereinafter referred to as the Strategy).

     2. The Government of the Republic of Kazakhstan, state bodies directly subordinate to and accountable to the President of the Republic of Kazakhstan, as well as central state and local executive bodies of the Republic of Kazakhstan:

     1) to develop and approve an Action Plan for the implementation of the Strategy within three months.;

     2) take other measures resulting from this Decree.

     3. Assign personal responsibility for achieving key indicators to the first heads of government agencies.

     4. Control over the implementation of this Decree is entrusted to the Administration of the President of the Republic of Kazakhstan.

     5. This Decree shall enter into force from the date of its signing.

President of the Republic of Kazakhstan

K. Tokaev

Approved by Decree of the President of the Republic of Kazakhstan on June 9, 2026 No. 1311

NATIONWIDE strategy of large-scale digitalization and total implementation of artificial intelligence technologies "Digital Qazaqstan" until 2029

     Content

     1. Introduction

     2. Analysis of the current situation

     2.1. Digitalization in the interests of citizens

     Human capital: education, skills, employment

     Healthcare

     A safe and comfortable living environment

     Public services and social support

     2.2. Digitalization in the interests of business and economy

     Digitalization of industries

     Tax administration

     The financial sector

     Development of the national IT industry

     The New Economy

     2.3. Digitalization of the state apparatus

     3. Main provisions: purpose and principles, vision and approaches to the development of digitalization and artificial intelligence

     3.1. Purpose and principles

     3.2. Vision and approaches to development

     3.3. System integration of advanced world practices into the national ecosystem of artificial intelligence

     3.4. Strategic directions of implementation, ways of achievement, key performance indicators (KPIs) and prospects

     Strategic direction 1. Digitalization and implementation of artificial intelligence in the interests of citizens

     Human capital development and the system of continuous competence formation

     Unified digital Health Management System

     A modern and sustainable environment for life and development

     Data-based public services and targeted social support

     Strategic direction 2. Digitalization and the introduction of artificial intelligence in the interests of business and the economy

     Digital transformation of key industries

     An intelligent model of tax administration

     The financial sector

     Development of a competitive IT industry

     Formation of a new economy

     Strategic direction 3. Digitalization and implementation of artificial intelligence in the state apparatus

     4. Conclusion

     1. Introduction

     The nationwide strategy for large-scale digitalization and total implementation of artificial intelligence technologies "Digital Qazaqstan" until 2029 (hereinafter referred to as the Strategy) is a program document defining the goals, objectives and priorities of state policy in the field of digitalization and the introduction of artificial intelligence (hereinafter referred to as AI).

     The strategy is based on a comprehensive analysis of economic and technological processes, current structural challenges of the national economy, a coordinated position of government agencies and organizations, as well as best international practices and expert approaches, aimed at a deep systemic transformation of Kazakhstan to transition to a full-fledged digital state over the next three years and the large-scale introduction of AI in all key sectors of the economy and the state apparatus. The implementation of the Strategy will ensure productivity growth, strengthen technological sovereignty and increase the standard of living of citizens, laying the foundation for the country's long-term competitiveness in the age of AI.

     International practice shows that digitalization and AI have become the basic factor of national competitiveness. Value in the economy is increasingly being created through digital platforms and AI solutions, and the government is building an ecosystem of rules, data, and platforms. Large-scale investments in digital infrastructure, human capital, and the institutional digital environment are among the key factors for accelerated economic growth and increased national competitiveness.1

     Thus, the United States of America has achieved a significant gap in terms of labor productivity through consistent investments in information and communication infrastructure and the creation of a favorable regulatory environment for innovation. At the same time, Singapore, South Korea, and Estonia are moving from fragmented automation to a platform-based digital economy, where data and AI are used as strategic assets, and the state forms a unified environment of rules, data, and digital platforms.

     Thus, international experience demonstrates that digitalization and AI maximize their impact not as a set of individual IT projects, but as an integrated national transformation encompassing the state, economy and people. It is this systematic approach that ensures productivity growth, technological sovereignty and long-term competitiveness of the country.

     Today, Kazakhstan is on the threshold of a unique historical window of opportunity. The country, with its advantageous geographical location, significant resource base, educated population, and significant progress in the field of digitalization, has all the necessary prerequisites to strengthen its position among the TOP global digital leaders.

     However, the current pace of digitalization is not enough to sustainably strengthen the country's leadership and reach the level of full-fledged global digital competitiveness, which necessitates the development of a Strategy that meets new challenges.

     The Strategy is a logical continuation and tool for implementing the strategic guidelines of the National Development Plan of the Republic of Kazakhstan until 2029, aimed at building a modern, innovative and sustainable state in a new technological reality where digital technologies and AI transform the economy and society. The strategy forms a broad system outline for the current AI ecosystem, which developed during the implementation of the Concept of Artificial Intelligence Development for 2024-2029, which laid down the basic principles and directions for the formation of national AI policy, as well as the tasks that were laid down by the Concept of Digital Transformation, the development of the information and communication technology and cybersecurity industry for 2023 - 2029 years.

     Key cybersecurity measures are set out in the National Security Strategy for 2026-2030 (approved by the Head of State on April 10, 2026), which, in the context of the intensive introduction of digital technologies and AI, provides for an integrated approach to protecting the digital environment and developing human resources, including issues of digital security, including the security of AI technologies. At the same time, cybersecurity measures provided for by the Concept of Digital Transformation, Development of the Information and Communication Technologies and Cybersecurity Industry for 2023-2029, initially designed for a three-year implementation period, will be integrated into the provisions of the National Security Strategy for 2026-2030.

     This Strategy serves as a tool for implementing the instructions of the President of the Republic of Kazakhstan, set out in his Message to the People of Kazakhstan dated September 8, 2025, "Kazakhstan in the era of artificial intelligence: current challenges and their solutions through digital transformation."

     The strategy is a system document aimed at ensuring the timely adaptation of the country to new technological realities, and in a number of areas - at shaping advanced development and strengthening Kazakhstan's competitive position in the global digital economy.

     The implementation of the Strategy will strengthen national competitiveness, increase technological sovereignty and make a leap in productivity growth through a comprehensive digital transformation of economic sectors.

     Based on international experience, the leading countries in terms of the development of the digital economy (included in the top 10 of the IMD2 rating) invest in digital technologies, including computing machinery and equipment, software and databases, at an average level of about 1.8% of GDP per year3, whereas for the countries included in the top 30 (from 11th to 30th place), this indicator is about 1.2% of GDP. Taking into account the position of the Republic of Kazakhstan (39th place in the IMD rating) and the GDP of about 300 billion US dollars, the forecast for a comparable investment level will be from 3.5 to 5.5 billion US dollars per year, which is equivalent to 10.5 - 16.5 billion US dollars over a three-year period4.

At the same time, one of the basic principles of the Strategy's implementation is reliance on market mechanisms and private initiative. This makes it possible to reduce the budget burden, create sustainable market incentives, accelerate the development of a competitive national IT industry and ensure a long-term multiplier effect. Financing of the Strategy's implementation will be based on a mixed model, including extra-budgetary sources, private investments, public-private partnership mechanisms, offtake contracts, co-financing, grant and venture capital instruments, as well as resources from development institutions.

     Infrastructure initiatives with commercial potential, application services, AI solutions, and industry-specific digital tools will be implemented with the involvement of private capital and market mechanisms, including public-private partnerships, long-term contracts with key customers, guaranteed demand, offtake contracts, co-financing, and the involvement of private suppliers. Regulatory and financial support tools, including subsidizing the implementation of digital solutions and concessional financing, will be used to stimulate the digitalization of key sectors of the economy.

     The development of the IT industry, startups, and new technology markets will be supported through grant, venture, and co-investment tools, acceleration programs, piloting, and subsequent scaling of successful solutions.

     Budget financing will be directed primarily to basic government digital components, including state registries, basic components of e-government, government APIs, and cybersecurity of government information systems.

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     1Global Digitalization Index (GDI, 2024)

     2 IMD Digital 2025 Rating https://www.imd.org/centers/world-digital-ranking /#:⁓:text=7%20th,%E2%88%925

     3 OECD data on investments in computing machinery and equipment, software and databases (investments in ICT excluding investments in telecommunications infrastructure) in 2020 – 2024 https://goingdigital.oecd.org/en/indicator/30 ?

     4 Indicative assessment: in order to form an accurate investment level, it is necessary to work out the capital expenditures for projects, the necessary resources, the financing structure, as well as an assessment of market capacity and the possibility of implementing initiatives

     2. Analysis of the current situation

     The results of the implementation of previous government programs, including Digital Kazakhstan (implemented in the period 2018-2022), confirm the country's progress in shaping the digital ecosystem. Kazakhstan has strengthened its position in key international rankings and is currently included in the group of countries with a high level of digital readiness according to the ICT Development Index of the International Telecommunication Union. In the IMD (World Digital Competitiveness Ranking 2025) world ranking of digital competitiveness, the country took 39th place,5 reflecting the ability of the national economy to implement and scale digital technologies.

     In the United Nations global e-government Development Index, the country rose to 24th place among 193 countries6, demonstrating a high level of digital governance maturity, and according to the Online Services Index, it entered the top ten countries in the world in terms of the quality of digital services.

     In addition, Kazakhstan ranks 58th out of 195 countries and is the leader among Central Asian countries in the Government AI Readiness Index 20257. These positions attest to the international recognition of the country's institutional efforts in the field of digitalization, the effectiveness of public administration and the established framework for technological development.

     Internal indicators also confirm the high level of digital maturity of the country. The share of electronic government services reached 92%.8 The share of non-cash payments (in retail trade) was about 90%.9 The share of e-commerce in 2024 was 14.1%.10 The share of Internet users in 2024 reached 95.3%11, while the number of specialists in the field of information and communication technologies and the digital economy increased to 200.5 thousand people, forming a large-scale national human resource potential and a stable foundation for the transition to the economy of data and AI.

     At the technological level, the country has made a qualitative leap: the national supercomputer "Alem.Cloud" and the supercomputer of the Kazakhtelecom joint-stock company "Al-Farabium" have been launched, taking respectively the 86th and 103rd positions in the global rating of TOR50012.

     In recent years, Kazakhstan has established an institutional and technological framework for the development of AI and the digital economy. The state is consistently building a comprehensive regulatory architecture, infrastructure, and competencies aimed at the large-scale introduction of intelligent technologies and the development of the country's advanced computing capabilities. As part of this policy, the Law of the Republic of Kazakhstan "On Artificial Intelligence" and the Digital Code have been adopted, and the international AI center "Alem.AI", a national AI platform has been formed for the implementation of intelligent solutions in public administration and economics. Progress has been made in the development of large language models: in 2025, two Kazakh-language models "KazLLM" and "AlemLLM" were presented, designed to develop AI and digital solutions in the Kazakh language. In order to strategically develop this area, Decree No. 881 of the President of the Republic of Kazakhstan dated May 19, 2025 established the Council for the Development of Artificial Intelligence under the chairmanship of the President of the Republic of Kazakhstan with the participation of leading international experts, which ensures the development of strategic solutions in the field of AI.

     At the same time, the experience gained in the field of digitalization shows that further development cannot be achieved solely through the introduction of individual technological solutions. The effectiveness of transformations is determined by their consistency and ability to cover key areas of society.

     The global dynamics of the introduction of generative AI shows that the key factor in competitiveness is not only the availability of models, but also the speed of mass technology adoption by people of working age. According to the Microsoft AI Economy Institute report, the global diffusion of generative AI in the second half of 2025 increased from 15.1% to 16.3% (every sixth inhabitant of the planet uses GenAI products), while growth is moderate and uneven. At the same time, the digital divide is widening: in the countries of the global north, the diffusion rate of generative AI reached 24.7% (an increase of 1.8 percentage points), in the countries of the global south - 14.1% (an increase of 1.0 percentage points), and the gap increased from 9.8 to 10.6 percentage points, reflecting the faster introduction of generative AI in developed economies and the risk of perpetuating long-term technological inequality. The situation in Kazakhstan is characterized by a level below the global average: in the second half of 2025, the indicator was 13.7% (in the first half - 12.7 %; growth +1.1 percentage points), which is lower than the global average of 16.3% and significantly lower than in developed countries13. In a regional comparison, with a generally low base of penetration of generative AI in Central Asian countries, Kazakhstan occupies a leading position both in Central Asia and among the countries of Eurasia. However, there remains a risk of further widening the gap with the outperformance of the countries of the global north. This means potential losses in labor productivity growth, risks of insufficient human capital development and increased external technological dependence, as well as the need to move from targeted initiatives to systemic measures to accelerate the diffusion of generative AI in public administration and the economy.

     The analysis of citizens' appeals in the e-Otinish system shows that the largest number of appeals is concentrated in the basic areas of everyday life. These include: healthcare, social protection, education, public and road safety, as well as issues related to customs and tax administration, construction, and housing and communal services. It is in these sectors that citizens and businesses most often face administrative barriers, complex procedures, insufficient transparency of processes and long deadlines for consideration of issues. This, in turn, confirms the need for comprehensive modernization of these industries, including the revision of business processes, the introduction of digital solutions and AI technologies, as well as increasing transparency and management efficiency.

     In the context of the global transition to a data economy and AI, digital transformation is becoming a driver of national development. That is why this Strategy is built around three key target groups - citizens, the economy and business, as well as the state apparatus.

     This approach reflects the fundamental logic of national development: the state forms an institutional digital environment, the economy and business ensure the introduction of technology and productivity growth, and citizens act as key beneficiaries and active participants in digital transformation.

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     5 IMD World Digital Competitiveness Ranking (2024). https://imd.widen.net/content/xclarczvwr/pdf/WDCR_Report_2025.pdf

     6 The UN E-Government Development Index. https://publicadministration.un.org/egovkb/en-us/data-center?

     7The Government AI Readiness Index. https://oxfordinsights.com/wp-content/uploads/2026/01/2025-Government- AI-Readiness-Index-Report_01_26.pdf

8https://primeminister.kz/news/memlekettik-kyzmetterdegi-innovatsiyalar-el-azamattary-men-bizneske-amalgan-zhana-tsifrlyk-sheshimder-29877

     9https://nationalbank.kz/kz/news/elektronnye-bankovskie-uslugi/17371

     10https://stat.gov.kz/ru/news/ob-elektronnoy-kommertsii-v-respublike-kazakhstan1/

     11https://stat.gov.kz/ru/industries/business-statistics/stat-it/dynamic-tables/?period=year

     12TOP500 Supercomputer Ranking. https://top500.org/statistics/sublist/

     13Microsoft AI Economy Institute. https://www.microsoft.com/en-us/research/wp-content/uploads/2026/01/Microsoft-AI-Diffusion-Report-2025-H2.pdf

     2.1. Digitalization in the interests of citizens

     Kazakhstan approached the beginning of the implementation of the new Strategy with a well-formed digital base: a significant level of Internet penetration, massive use of electronic government services and advanced mobile services. This creates the basis for further development and objectively allows us to move from the stage of digitalization of individual processes to a more complex human-centered model of the digital state.

     International analysis, including research by the Organization for Economic Cooperation and Development (OECD), confirms the principle of human-centricity of digital transformation, demonstrating that its effects manifest themselves at the main stages of citizens' lives.

     In this context, a citizen is considered not as a user of individual services, but as a subject of a continuous life cycle - from preschool development to professional realization and active longevity. This makes the gap between digital services and the real logic of human life a key challenge. In fact, today, citizens need to independently interact with disparate departmental processes, faced with data duplication, manual procedures, and the lack of end-to-end scenarios. Kazakhstan has taken the first steps in providing proactive social support. Based on Smart Data Ukimet, a system for analyzing more than 100 key indicators is being implemented, on the basis of which more than 4.5 million citizens received proactive services, and 52 thousand citizens improved their overall well-being through the "Digital Family Card" in 202514.

     However, most of the obstacles to further expansion of proactive support have common causes such as insufficient data connectivity, a reactive service delivery model instead of a proactive one, gaps between the education system and the labor market, uneven infrastructure quality, and limited personalization of services.

     Human capital: education, skills, employment

     Human capital is a key asset of Kazakhstan's competitiveness in the age of AI. The country has an infrastructure for the formation of competencies at all stages of the human life cycle - from early development to professional and scientific activities. However, today the digital infrastructure that ensures the development of human capital functions primarily as a set of disparate subsystems poorly integrated by unified data, end-to-end development trajectories and a focus on measurable results.

     There are over 12,000 organizations (kindergartens and mini-centers) at the preschool level, where digitalization is mainly limited to accounting and administrative processes (priority, reporting, registration). The tools for forming an early personalized trajectory of a child's development are applied pointwise and do not form a systematic practice, which reduces the likelihood of identifying talents at an early age.

     There are 8,029 schools with more than 3.9 million students at the secondary education level, where basic competencies are formed and the foundation for the future human resources potential of the country is laid.

     In recent years, progress has been made in the development of the digital infrastructure of the education system: more than 98% of schools are connected to the Internet, and educational platforms have been deployed. However, with this scale of the system, differences remain in the quality of education and the level of digital equipment between urban and rural schools. In addition, digital tools are in many cases used primarily as a means of electronic support of educational processes for accounting, content distribution and communication, while their potential for improving the quality of education and personalizing educational trajectories is not fully realized (accounting, content, communication).15

     The level of technical and vocational education includes 763 organizations with a contingent of 556,000 students, and higher education is represented by 113 universities with 753.1 thousand students. At the same time, 84% of universities have implemented AI disciplines and 42 educational programs on AI, in 2025 about 670 thousand people completed educational courses on AI under the AI-SANA program. Despite the ongoing work, there remains a structural gap between educational programs and the real needs of the economy. Employers' requests and applied graduate training are not synchronized enough, and the system itself is still using limited data to predict the shortage of competencies and promptly update programs. As a result, staff graduation does not always translate into sustainable employment and productivity growth, which reduces the return on investment in education in an accelerated technological transition.

     425 research organizations and about 23,000 scientists are engaged in scientific activity, but it remains poorly integrated with university education and industry. The lack of a unified digital logic for prioritizing research, managing competencies, and implementing results limits technology transfer and the practical impact of scientific development16.

     A separate systemic challenge is related to the labor market, where employment is increasingly shifting towards flexible and platform-based solutions that are not yet sufficiently integrated into the system of labor relations and social protection. This increases the vulnerability of citizens, reduces the stability of labor trajectories and creates risks for the long-term quality of human capital.

     Healthcare

     In recent years, the healthcare system of the Republic of Kazakhstan has undergone a stage of large-scale digitalization of basic processes, as a result of which a unified infrastructure framework for digital healthcare has been formed.

     Medical digital systems have been implemented at all levels of medical care, providing records of services rendered, electronic medical records management and integration with government digital platforms. At the same time, the main focus of digital solutions is focused on accounting, reporting and financial calculations of medical care, while the potential of accumulated significant amounts of clinical and administrative data for strategic management, forecasting and improving system efficiency has been partially realized.

     Tools for forecasting, scenario analysis, and assessing the impact of management decisions on public health indicators are in their infancy. Thus, the lack of uniform standards for data storefronts and centralized analytical models limits the use of data in the process of strategic planning and interagency interaction.

     The digital architecture of the industry was formed in stages and mainly in the logic of solving individual functional tasks. As a result, several key information circuits have been created to ensure the fulfillment of regulatory and operational functions. However, a single end-to-end data and process management architecture has not yet been fully developed.

     Digital healthcare facilities primarily interact at the level of messaging and reporting data, while integration at the level of clinical, management, and analytical models is limited. This reduces the possibility of forming a single digital representation of the healthcare system as an object of management.

     In order to ensure effective planning and forecasting of the required volume of medicines consumed, a mechanism has been introduced for planning personalized needs for medicines for patients registered at the dispensary. Patients registered at the dispensary receive their prescribed medications using a QR code without having to visit a doctor every time to receive a paper prescription. Nurses and pharmacists dispense drugs by scanning an electronic prescription in a "Social Wallet", which significantly speeds up the process and convenience of treatment. More than 85% of patients receiving free medicines are provided with them through digital mechanisms, including through a "Social Wallet".

     Since July 2024, Kazakhstan has introduced mandatory digital labeling of all medicines and medical products for traceability of their movement. Each product unit receives a unique code, which allows you to track the path "from the factory to the patient." The introduction of labeling has ensured transparency of drug turnover and reduced the risks of counterfeiting.

     At the current stage, healthcare digitalization is still limited to ensuring transparency and accounting of medical care processes, but not to data-based management. Digital systems have little impact on program evaluation, resource allocation, and task prioritization. Management decisions continue to rely on aggregated statistics rather than operational and predictive analytics.

     AI technologies are considered as a promising direction for the development of the industry, however, their implementation is mainly pilot and local in nature. The main constraints are not the lack of technology, but the insufficient readiness of the institutional, architectural and regulatory environment for the large-scale use of AI in the interests of the healthcare system.

Thus, the digital transformation of healthcare in the Republic of Kazakhstan is moving from the stage of technological implementation to the stage of institutional and managerial formation. The key challenges are not the further digitalization of individual processes, but the formation of a holistic model of healthcare system management based on data, analytics and forecasting, including the use of AI technologies as a tool of public policy.

     A safe and comfortable living environment

     Elements of the "smart" infrastructure are being implemented at the regional and city levels. Intelligent video monitoring systems, digital tools for managing transport, housing and communal services (hereinafter - housing and communal services) and public safety have been introduced in a number of cities. These solutions are already showing measurable effects. There is a steady decrease in the level of criminal offenses: in 2025, more than 123 thousand criminal offenses were registered, which is 6% lower than the same period of the previous year17. Video surveillance systems have been deployed in a number of regions, more than 1.6 million cameras have been installed, and separate analytical modules have been implemented, which already has a measurable effect on detection and prevention of offenses.

     In the field of transport and urban mobility, Kazakhstan is facing an increasing burden on the road network and public transport amid accelerated urbanization and the growth of its fleet, which already exceeds 5 million registered vehicles.18 Despite the implementation of individual infrastructure projects in large agglomerations, transport systems remain fragmented, characterized by limited use of intelligent flow management, unified digital platforms and predictive analytics, which leads to congestion, increased accidents and reduced availability of urban services.

     Systemic infrastructure problems remain in the housing and communal services sector: a significant part of the engineering networks is physically worn out (in some regions, the wear of heating and water supply networks exceeds 50-60%), the accident rate remains high, and facilities are managed mainly manually. Digitalization of housing and communal services is fragmented, and data on resource consumption, network maintenance, and accidents are scattered among service providers, akimats, and utilities and are not integrated into a single analytical framework. The lack of intelligent accounting and predictive monitoring leads to inefficient consumption of water, heat and electricity, increased operating costs and a decrease in the quality of services for the population. As a result, housing and communal services remains one of the least mature industries in terms of digitalization, where there are chronic risks to a comfortable environment and the sustainability of urban infrastructure.

     Ensuring the quality and sustainability of Internet access remains a separate system challenge. With Internet penetration approaching 92%, there remains a pronounced digital disparity in terms of speed, stability, and actual connectivity. In rural and remote settlements, along transport corridors, as well as in tourist areas, high-speed Internet is still characterized by instability or limited bandwidth.

     The persistence of such practices leads to the fact that a significant part of urban and communal tasks are solved using local (non-platform) solutions developed at the level of individual akimats. This, in turn, limits the ability to scale successful practices, complicates interagency integration, and makes it difficult to objectively assess the effectiveness of measures taken.

     Public services and social support

     Public services in Kazakhstan demonstrate a high level of digitalization: more than 93% of application forms have been converted to electronic format on the eGov platform and in the eGov Mobile mobile application. Today, out of 1,467 public services, 90.4% are available online, and 90.6% of services are available from a smartphone, which makes the process as convenient as possible for citizens. 39 types of digital documents have been introduced, completely replacing paper counterparts.

     Despite the significant volume of public services provided in digital format, life situations are insufficiently integrated into one end-to-end digital process and continue to be fragmented into dozens of separate applications and documents requiring the input of the same data due to insufficient interdepartmental integration.

     A significant limitation is institutional motivation. Government agencies demonstrate insufficient involvement in the interagency cooperation necessary for the digital transformation of public services. Digitalization is often seen as the automation of bureaucratic processes, rather than rearranging the logic of providing services for the convenience of the citizen. Departmental digital initiatives remain fragmented, with their own registries and business processes, which prevents the formation of an integrated digital contour for citizens.

     Challenges remain in the field of labor and employment related to determining the real level of employment, income of citizens and their social status. The fragmentation and incomplete integration of data on employment, income, and family composition make it difficult to form a holistic and objective picture of the level of well-being of citizens, which limits the ability to make accurate and timely management decisions. This has a direct impact on the effectiveness of the social support system, where there are still problems with the accuracy and targeting of aid recipients. Data analysis on income, employment, marital status, and real needs of citizens is used to a limited extent, which reduces the efficiency of resource allocation and leads to cases where government assistance is provided to those who are less in need of support, while the most vulnerable categories of the population do not receive it in full or with delays.

     Another type of public service is a socially significant service that has a number of features. If classical public services are often transactional in nature (request - response), then socially significant services ensure the systemic vital activity of society, respectively, they are provided to the whole society as a single social organism.

     The legal nature of socially significant services is closely linked to the principle of the indivisibility of public goods. Unlike individually oriented services such as passport issuance or marriage registration, socially significant services are used collectively (protection of public order, sanitary and epidemiological welfare of the population, provision of high-quality drinking water, street lighting, garbage collection, etc.). The continuity inherent in the definition means that the state is obliged to provide these services 24/7, regardless of the individual request of a particular individual or legal entity. This places an increased responsibility on government agencies for the sustainability and quality of these processes.

     Today, the Register of Public Services includes 6 types and 29 subspecies of socially significant services that do not cover all areas of interaction between the state apparatus and the public.

     2.2. Digitalization in the interests of business and economy

     With limited resources and an accelerating technological transition, the digital transformation of the economy requires prioritization. The economy of Kazakhstan is characterized by a high sectoral concentration: about 70% of GDP is formed by such sectors as the oil and gas sector and subsoil use, industry, transport and logistics, the financial sector, construction, the agro-industrial complex (hereinafter referred to as the agroindustrial complex), as well as the segment of small and medium-sized businesses (hereinafter referred to as SMEs), which is the main source of employment.

     According to official statistical information from the Bureau of National Statistics for 2024, the extractive industry and the oil and gas sector account for 16.3% of GDP and over half of the country's export revenue, the manufacturing industry accounts for 12.4% of GDP, transport and logistics 5.7%, creating critical infrastructure for transit potential, the financial sector 3.4%, construction 6%, agriculture 5.6%.19, while SMEs form 38.9% of GDP,20 and provide employment for almost half of the economically active population. It is these industries that determine the macroeconomic stability, investment attractiveness and long-term productivity growth of the economy.

     Business system barriers are end-to-end in nature: tax administration, licensing procedures, access to infrastructure, subsidies and financing, as well as fragmentation of industry data remain key sources of transaction costs. Business is particularly sensitive to tax administration issues as the main point of contact between the state and the economy, where manual processes, reactive control and limited use of risk-based and predictive analytics remain.

     Along with the modernization of traditional industries, it is necessary to form new areas of economic growth. The accelerating technological transition requires, at the current stage, laying the foundations for a future economy focused on AI, data, and high-tech markets, which will ensure long-term sustainability, diversify sources of added value, and reduce dependence on raw materials.

     Digitalization of industries

Today, digitalization is largely carried out at the level of individual enterprises and departments, while there are no single end-to-end industry platforms with common data standards, measurable performance indicators and built-in integration with regulatory circuits. There is a fragmentation of the implementation of digital registers in relevant departments. The digital transformation of industries should focus not on the number of information systems implemented, but on the depth of integration of digital solutions into key value chains, as well as the completeness of industry coverage with digitized, interagency-coordinated and compatible data and business processes that ensure managerial decision-making.

     The oil and gas sector and subsurface use form the basis of the country's export earnings and currency stability. At the same time, the digital transformation of the industry remains fragmented and concentrated mainly within large operators, without forming a single national resource management contour. The key system gap is related to the lack of an end-to-end digital architecture "subsoil – mining - transportation - processing - export". Geological data, production indicators, production accounting, environmental monitoring and fiscal information exist in disparate systems of companies and regulators, which limits the transparency of processes, makes it difficult to predict reserves and reduces the manageability of the industry at the state level. A separate problem remains the actual lack of mass instrumentation for the production and movement of hydrocarbons and solid minerals at all stages of the production chain. This creates accounting risks, reduces the accuracy of tax administration, and limits the possibilities of digital control. Collectively, the industry operates in a logic of reactive control rather than predictive resource management.

     In the energy sector, a significant part of the generating capacities is characterized by a high level of physical wear and tear, which leads to a decrease in available capacity, an increase in accidents and an increase in unplanned repairs. The systemic imbalance is intensifying, and dependence on external balancing and the purchase of capacity reserves is increasing. The electric grid infrastructure in a number of regions does not provide the required bandwidth to connect new generation sources and cover growing consumption, including promising energy-intensive digital clusters and data centers. High wear of distribution networks is accompanied by increased energy losses and reduced reliability of energy supply. A significant limitation remains the insufficient level of digitalization and observability of the energy system, expressed in the absence of end-to-end telemetry, integrated data and analytical tools necessary for operating modes management, balancing and investment planning.

     Industry remains one of the key drivers of the economy. However, the digital transformation of industry is developing unevenly and is mainly localized in individual large enterprises, without forming a single industrial digital circuit at the national level. Most enterprises continue to operate in a model of disparate automated sites: separate SCADA systems, ERP or local MES solutions are being implemented, but data on capacity utilization, downtime, product quality and energy consumption are not combined into a single analytical space. This limits the possibilities of operational management of production processes and reduces the transparency of the industry for the government and investors. A significant part of the equipment remains morally and physically obsolete, and the level of equipment with sensors and the industrial Internet of Things (IoT) remains low. As a result, asset status monitoring is carried out mainly manually or on the basis of periodic reporting. This leads to unplanned downtime, losses of raw materials, as well as an increase in the cost of production.

     Kazakhstan's transport and logistics sector is a key element of the country's economic connectivity and transit potential. The main Eurasian corridors pass through the country's territory, and logistics ensures the functioning of industry, agriculture and foreign trade. At the same time, the industry is developing as a collection of disparate solutions from individual operators, departments, and infrastructure hubs. Data on cargo movement, infrastructure loading, downtime, terminals, warehouses, and border procedures remain distributed among the chain participants and do not form a unified picture of movement in real time. Electronic documents, tracking, and customs procedures work in fragments and are not integrated into a single digital circuit. This results in the retention of a significant proportion of manual operations, reduces the predictability of delivery times, and leads to increased transaction costs for businesses. Bottlenecks at the junction of multimodal transportation remain particularly sensitive, where the lack of predictive analytics and digital planning leads to the accumulation of wagons, cargo downtime and inefficient use of capacity. A separate limitation is the weak integration of logistics with industrial, agricultural and financial circuits.

     The financial sector demonstrates a high level of digital maturity of banking ecosystems and fintech services, including through close cooperation with the government. At the same time, non-bank financial instruments (leasing, factoring, export financing, and alternative payment solutions) are underdeveloped, which creates risks of uneven development of the financial ecosystem and may be a deterrent to competition. Financial data remains mostly closed within banking platforms, limiting the possibilities of end-to-end credit and insurance support for projects.

     In the context of growing cross-border capital flows and increasing digital risks, financial management relies on an actively developing digital supervisory infrastructure, including the use of AI-based solutions for risk assessment and monitoring. Supervisory tools are being consistently strengthened with a focus on increasing efficiency and bringing analytics closer to real-time. At the same time, the current architecture is mainly focused on individual sectors of the financial market and does not yet fully provide end-to-end, intersectoral analysis of transit schemes, related counterparties and behavioral patterns, which limits the transition to a full-fledged predictive risk management model.

     The construction sector remains one of the most inert sectors of digital transformation. Despite the availability of mature technologies (SIM modeling, digital object doubles, electronic expertise, online permissions), their practical implementation is fragmented. The processes of design, approval, expertise and commissioning of facilities are still largely based on paper and semi-digital procedures, and there is no single digital chain "project- permit- construction - commissioning". A significant part of the approving authorities remains focused on manual procedures and departmental regulations, which leads to a delay in the review of project documentation, construction permits and connection to utility networks. The cumulative cycle of approval procedures for large facilities can be more than 6-9 months, despite the formal availability of electronic services. Digital platforms in construction are used primarily as filing tools, rather than as tools for managing the life cycle of an object. Data on land plots, urban planning regulations, engineering infrastructure, and the actual progress of construction remain disconnected between local executive authorities, expert organizations, and public utilities, which creates opacity in processes, increases transaction costs, and creates risks of corrupt practices. As a result, the industry is facing limited productivity growth, slower commissioning of facilities, and barriers to attracting investment.

     The agro-industrial complex remains one of the most subsidized, but at the same time the least mature sectors of the economy in terms of digitalization. Agricultural productivity remains significantly lower than in comparable countries. The average grain yield in Kazakhstan ranges from 14-18 c/ha, in individual farms 20-30 c/ha, while in comparable OECD countries such as Canada, similar indicators reach 30-40 c/ha, reflecting a structural gap in technology, management and data use. Despite the availability of solutions for improving agricultural efficiency, satellite monitoring, digital field maps and agroanalytics, their application is spot-based and not integrated into mass practice. Most farms continue to operate without systematic consideration of soil agrochemistry, weather data, crop productivity and the state of technology, which makes production dependent on weather factors and manual management decisions. A similar situation is observed in animal husbandry. There are no unified digital profiles of livestock, end-to-end accounting of productivity, veterinary status and feed supply. Animal health, reproduction, and product output are monitored mainly in fragments, without the use of sensors, biometric solutions, and predictive analytics. This limits the possibilities of early detection of diseases, increasing productivity, and managing the genetic potential of the herd.

The quality of government support measures remains a separate problem. There are no end-to-end digital profiles of farms, unified databases on yields, land use efficiency, livestock productivity, and actual budget returns. The chains "field - farm - storage - processing - logistics - export" remain broken.

     SMEs, as a key source of employment and competition, are growing quantitatively, but are facing high regulatory and transactional pressures. According to official statistical information from the Bureau of National Statistics, as of January 1, 2025, 2.27 million SMEs were registered, of which 2.1 million were active, and 4.4 million people were employed in SMEs.21 At the same time, the digitalization of SMEs is limited by access to individual services, while the key need is to reduce regulatory costs and transition to "smart" compliance, including pre-filling, proactive notifications, unified digital profiles, predictive risk management instead of reactive control.

     Tax administration

     The tax system of Kazakhstan remains a key point of contact between the state and the economy.

     Tax authorities process tens of millions of declarations, invoices, and reporting forms annually, with a significant portion of the processes converted to electronic format. At the same time, the achieved level of digitalization has not transformed tax administration into a business support service system.

     Despite the introduction of electronic invoices, online cash registers, and digital reporting, the tax circuit remains focused primarily on after-the-fact control rather than error prevention and monitoring of economic activity. Some taxpayers continue to face additional charges, fines, and account freezes after transactions are completed, rather than at the planning stage.

     Despite the fact that government agencies, within the limits of their powers, are working to clarify regulatory legal acts applicable to specific entities or a specific situation, based on appeals from individuals and legal entities, an analysis of complaints filed through the e-Finish platform for 2025 shows that tax administration is among the three most problematic spheres. Today, businesses need help interpreting complex regulations and legislative changes.

     In the current configuration, tax administration remains digital in form, but control in essence. Without the transition to the "taxes as a service" model using AI for predictive analytics, automatic monitoring of business operations, and integration with industry platforms, the tax contour will continue to be a source of administrative burden rather than a growth incentive tool.

     The financial sector

     Kazakhstan's financial sector has entered a stage of accelerated technological and institutional transformation. Its development is simultaneously influenced by the growth of geopolitical uncertainty, increased demands for sustainability and transparency, increased competition from BigTech, FinTech and RegTech players, as well as the rapid spread of generative AI as a tool to increase efficiency and change business models. Under these conditions, traditional approaches to digitalization based on disparate point-to-point solutions no longer provide the necessary level of flexibility, speed, and manageability of processes.

     The National Bank of the Republic of Kazakhstan and the Agency of the Republic of Kazakhstan for Regulation and Development of the Financial Market play a system-forming role in ensuring stability and confidence in the financial market. At the same time, the increasing complexity of the financial ecosystem, the growth of digital transactions and the emergence of new service delivery models are becoming prerequisites for the further development of modern digital surveillance tools, reducing excessive regulatory burden on market participants, as well as creating conditions for the safe introduction of innovations.

     However, there remains a need for a more coordinated development of key elements of the digital financial infrastructure. The priorities include strengthening national payment circuits, developing a unified approach to data management, increasing cyber resilience, and developing a systematic fight against fraud throughout the financial system. Without the formation of a single managed data space, large-scale implementation of SirTech and RegTech tools, as well as integrated predictive risk management mechanisms, further digitalization of the financial market will be fragmented and will not fully ensure its stability, security and competitiveness.

     Development of the national IT industry

     The IT market of Kazakhstan has demonstrated steady quantitative growth in recent years: the market volume exceeded 2 trillion tenge, exports of IT services increased from 60.07 million US dollars in 2021 to 690.7 million US dollars in 2024, amounting to 515.5 million US dollars in the first half of 2025, more than 2,000 companies, including about 465 startups with foreign participation.22

     The basic support infrastructure, accelerators, technology parks, tax incentives and individual venture capital instruments have been formed. The first globally competitive players are emerging, which confirms the presence of world-class entrepreneurial and engineering potential.

     At the same time, the market is still based on mature IT companies and system integrators, focused mainly on the development and maintenance of government information systems and outsourcing of digital projects. Despite the quantitative growth of the IT market and the formation of a startup ecosystem, the industry remains poorly integrated into the economic transformation of the country.

     Mature IT companies mostly work as government contractors, while startups are stuck at the pilot and prototype stages. The key systemic problem remains the lack of sustainable implementation financing, when pilot projects are launched but not paid for or scaled, which deprives the market of motivation to invest in product development.

     The government remains institutionally cautious about external technological solutions, resulting in the formation of its own digital teams developing products within the system. However, taking them beyond specific tasks creates direct competition for the private market, which fragments the ecosystem and increases the dependence of digitalization on budget cycles.

     Startups face barriers to entry into government and quasi-government procurement due to requirements for turnover, experience, and financial stability, and a significant number of teams are forced to focus on foreign markets or stop developing.

     Collectively, this creates a gap between the IT sector and the real economy: digital solutions are developing in isolation, industry data is not integrated into a single contour, and innovations do not reach large-scale implementation. Under the current model, the IT market remains a service market, not an industrial one.

     The New Economy

     A technological base has been formed in the Republic of Kazakhstan, which makes it possible to restructure the structure of the national economy with the inclusion of new high-tech industries with high added value. Basic digital infrastructure has been created, data processing centers and supercomputing capacities are being developed, and initiatives in the field of AI, digital financial instruments, unmanned systems, and space services are being implemented. Steps have been taken to create a regulatory environment for new technological directions.

     At the same time, additional systemic efforts are required to fully unlock new opportunities and form new high-tech sectors of the economy.

     The computing infrastructure is distributed among different operators and is not integrated into a single national infrastructure capable of providing industrial training of models, scaling of AI products and export of computing power. Access to high-performance resources is limited, dependence on foreign equipment and cloud solutions remains, and the need for further competence development creates risks of technological vulnerability.

     The segment of unmanned systems and autonomous mobility is at an early stage. The pilot solutions are not supported by a unified digital traffic management infrastructure, a standardized regulatory model, and scaling mechanisms. There is no systematic approach to the formation of a low-altitude economy and the integration of autonomous transport into the national transport system.

     The crypto industry and the digital asset market are developing as part of separate initiatives, including the regulation of digital financial instruments, but they are not yet integrated into a single financial and technological architecture of the country. The potential of asset tokenization and the formation of strategic digital reserves remain unrealized in full.

     Space services rely on existing infrastructure and international cooperation, but their contribution to the economy is limited. There is no export-oriented model for the development of orbital infrastructure and the integration of satellite data into industry-specific digital platforms.

     The robotization of industry is developing unevenly and mainly covers large enterprises. The level of automation and implementation of robotic solutions is significantly inferior to the technological leaders, which limits the growth of labor productivity and the global competitiveness of the manufacturing sector.

     Based on the existing prerequisites, the next stage should be the development of new sectors of the economy to form new sources of economic growth and consolidate Kazakhstan in global value chains.

The robotization of industry is developing unevenly and mainly covers large enterprises. The level of automation and implementation of robotic solutions is significantly inferior to the technological leaders, which limits the growth of labor productivity and the global competitiveness of the manufacturing sector.

     Based on the existing prerequisites, the next stage should be the development of new sectors of the economy to form new sources of economic growth and consolidate Kazakhstan in global value chains.

     2.3. Digitalization of the state apparatus

     The State apparatus functions as a set of vertically organized departmental institutions. Government agencies implement a significant number of administrative and interdepartmental procedures, based primarily on the logic of the distribution of powers between departments. At the same time, the real life situations of citizens and economic chains are horizontal and end-to-end. This discrepancy between the architecture of the state and the logic of life has led to the fact that digital solutions have historically developed as a reflection of individual functions of government authorities, rather than as a single platform for managing life scenarios and economic processes.

     As a result, the digitalization of the state apparatus for two decades has been implemented mainly through the automation of individual procedures. 517 information systems were created, a significant part of which developed in isolation according to the departmental principle with data duplication and a constant need for point integrations.

     Most systems are primarily focused on accounting and reporting, while analytical support for management decisions and evaluation of achieved results remain limited. A significant part of government IT solutions is built on a monolithic architecture and poorly adapted to scaling and implementation of modern technologies. The survey revealed the presence of outdated platforms, the lack of redundancy of critical infrastructure, limited system flexibility and increased risk of accidents. Critical limitations of the stability of the digital contour of the state have been identified, including the lack of full-fledged hot and cold backup centers and limited implementation of AI models and advanced analytics in the existing digital environment.

     Fragmentation is being reinforced by the parallel development of its own IT teams and platforms in central authorities, regions, and the quasi-public sector. This leads to an intersection with the functions of the private technology market. As a result, the government simultaneously acts as a customer, regulator, and executor, which distorts market incentives, reduces competition in quality, and displaces private IT companies and startups from large transformational projects. This model undermines the formation of a sustainable technological ecosystem, as innovations are locked within departments, and the market is deprived of scalable demand.

     In modern conditions, the productivity of the state apparatus remains limited. About 30 to 40% of government employees' working hours are spent on repetitive operational activities such as data collection, interagency coordination, and reporting. Digital tools have not yet become the basis of the "data - analysis - solution – result control" management cycle.

     Also, the very model of functioning of the state apparatus remains an institutional limitation of digital transformation. The government has two key change management tools at its disposal: regulatory regulation and budget planning. However, both mechanisms are focused on long approval cycles and are not adapted to the pace of technological change.

     In the context of accelerating technological development, a transition to digital and adaptive regulation is required. Normative activity should be based on the analysis of law enforcement data, economic effects and behavioral patterns, ensuring a reduction in the time required for the preparation of regulatory decisions and their timely correction. The use of AI will automate the identification of collisions, excessive requirements and regulatory burden.

     As a result, a structural gap is forming between the capabilities of digital solutions and the ability to quickly institutionalize and finance their implementation. A significant part of the projects remains at the pilot stage or loses relevance even before the completion of formal procedures.

     A separate systemic limitation remains the personnel contour of the digital transformation of the state apparatus. Despite the introduction of the institute of digital deputies (vice ministers), this institutional model has not yet been fully extended to all government agencies and organizations. Also, a number of strategically important enterprises lack dedicated digital transformation managers, which reduces the manageability of digital projects. An additional limitation remains the persistent shortage of key specialists - IT architects, data engineers, AI specialists, and product managers.

     From the point of view of the state apparatus, data management is currently characterized by fragmentation. Much of the data is stored in departmental circuits, is subject to duplication, and is used primarily for reporting purposes rather than for management decision support and forecasting. The data economy is in its infancy: there are no sustainable institutional and technological mechanisms for exchanging and reusing data to create added value. This limits the systematic use of analytics and AI as tools to improve the effectiveness of public administration.

     The lack of end-to-end analytics limits the government's ability to assess the actual impact of regulatory decisions on the economy and the quality of life of citizens. Regulation is often updated reactively, without a systematic assessment of accumulated effects. This creates a structural gap between the dynamics of technological change and the speed of adaptation of the legal environment.

     Cybersecurity remains a factor in the sustainability of the digital state. As digital services and personal data arrays grow, the number of cyber risks increases, while the level of security varies significantly between organizations. Cybersecurity is still perceived as an auxiliary function, rather than as a basic element of the architecture of the digital state, which increases the likelihood of large-scale incidents and undermining the trust of citizens.

     Technological sovereignty remains limited. A number of mission-critical systems depend on foreign platforms, licenses, and suppliers. This creates sustainability risks and makes digital transformation vulnerable to external constraints.

     __________________________

     14https://publicadministration.desa.un.org/blog/kazakhstans-digital-evolution-egov-ai-governance

     15https://primeminister.kz/news/reviews/bilim-beru-zhuyesindegi-reformalar-bolashakka-bagdar-zhane-kogamnyn-suranysy-30004

     16https://stat.gov.kz/en/industries/social-statistics/stat-edu-science-inno/dynamic-tables/

     17https://stat.gov.kz/industries/social-statistics/stat-crime/dynamic-tables/

     18https://stat.gov.kz/news/2024-zhyly-1-8-mln-k-lik-tirkeuden-tti/

     19https://stat.gov.kz/ru/industries/economy/national-accounts/dynamic-tables/

     20https://stat.gov.kz/industries/business-statistics/stat-org/publications/301717/

     21https://stat.gov.kz/ru/industries/businessstatistics/stat-org/publications/473784

     22https://primeminister.kz/ru/news/reviews/cifrovoi-kazaxstan-innovacionnye-reseniia-obespecat-rost-vo-vsex-sferax-ekonomiki-30625

     3. Main provisions: purpose and principles, vision and approaches to the development of digitalization and artificial intelligence

     3.1. Purpose and principles

     The aim of the Strategy is to position the Republic of Kazakhstan as a leading digital state with technological sovereignty, a developed data economy and a competitive AI industry that ensures sustainable growth in the quality of life of citizens, economic productivity and the effectiveness of the state apparatus.

     The strategy is aimed not only at digitalization of processes, but also at the transition to a new development model in which AI becomes the basic factor of economic growth and institutional sustainability. The implementation of the Strategy will ensure the formation of a new generation of digital economy, strengthen human capital and create infrastructure for long-term technological leadership.

     The strategy provides for the formation of a human-centered digital environment and end-to-end life trajectories of citizens from education and employment to healthcare, social support and algorithmic management of budgetary and tax mechanisms. AI is considered as a systemic technology for productivity growth in all key sectors of the economy.

     In parallel, the development of national computing infrastructure, cloud and hardware capacities, the formation of a data economy and new technology markets, including AI, robotics, autonomous systems, platform mobility and new generation digital services, will be provided. Special attention is paid to the development of the domestic IT industry, the support of the startup ecosystem and the formation of an internal market for scaling digital solutions.

     The objectives of the Strategy include:

     creating an end-to-end digital trajectory of a citizen that holistically combines education, skills, employment, healthcare, and a comfortable and safe living environment;

     the functioning of the economy as a system that logically links data, production, logistics, finance and taxes into a single digital chain using AI;

The functioning of the state apparatus is based on a single platform, where services are proactive, the budget is formed algorithmically, norms are modeled on data, and a national digital contour has been formed that ensures technological sovereignty and sustainability.

     The development of digitalization and AI is based on the following principles.

     1. The principle of economic efficiency suggests that digital transformation is seen as a tool for creating markets, returning investment, and increasing productivity. Each project should provide a measurable economic effect: generate income, reduce costs, or create an infrastructure to create added value. Priority is given to initiatives with proven economic returns, extra-budgetary financing (investments, offtakes and other financial instruments).

     2. The platform principle involves a shift from departmental fragmentation to a unified architecture of data and services in order to ensure the quality of digital services and reduce costs.

     3. The principle of human-centricity presupposes a focus on improving the quality of life of citizens, ensuring their well-being and expanding their opportunities throughout the entire human life trajectory.

     4. The principle of responsible and ethical use of digital technologies assumes that the use of digital technologies and AI is based on the principles of transparency, explainability, non-discrimination, protection of digital rights, forming a stable architecture of trust between the state, citizens and business.

     5. The principle of security and technological sovereignty implies a focus on data protection, infrastructure sustainability, and the development of national solutions.

     6. The principle of adaptive regulation involves ensuring the flexibility of the regulatory system based on a continuous analysis of law enforcement practice and a digital assessment of regulatory impact.

     7. The principle of differentiated digitalization implies that information processes will be centralized on single platforms, depending on their characteristics, and processes requiring physical presence and local context will be managed locally with the supporting role of IT.

     3.2. Vision and approaches to development

     As part of the Strategy, a holistic vision of the digital state is being formed as a long-term model of the country's development, defining the logic of transformation of the state apparatus, economy and social sphere in the context of accelerated technological development and widespread adoption of AI. This vision sets a single guideline for government institutions, business and society, and serves as the basis for developing coordinated solutions in three key areas of the Strategy's implementation: improving the quality of life of citizens, ensuring sustainable economic growth and business prosperity, and the effectiveness of the state apparatus.

     A digital state is a fair, proactive state based on data management, in which services and processes operate using effective AI, the economy develops through technology and innovation, the rights and security of citizens are reliably protected, and every person and business has equal digital opportunities for growth and well-being.

     Such a state considers improving the quality of life of citizens as one of its main priorities and is built around a personalized human life trajectory, perceiving it as an integrated system of data and solutions, covering education, competence formation, employment, income, health, social stability and legal protection, provided on the basis of objective analysis and use of data. Personalization is becoming a basic principle of public policy: from education with dynamic learning trajectories, forecasting the demand for skills and reducing the proportion of unclaimed graduates to preventive healthcare and prevention based on risk analysis. The use of data makes it possible to increase social sustainability, reduce systemic risks, and strengthen public confidence in government decisions through transparency, explainability, and non-discrimination of algorithms, while giving absolute priority to security, privacy, and digital rights of citizens.

     The economic dimension of the digital state relies on data, algorithms, platforms, and competencies as key intangible assets of the new economy. Economic growth is ensured through the development of platform ecosystems in which government and business interact in a digital environment, rather than through disparate departmental circuits. The focus is shifting to industries that are generators of added value and productivity, including energy, industry, transport and logistics, agro-industrial complex, construction and financial markets, as well as the formation of new growth sectors related to digital logistics, platform employment and the data economy. Artificial intelligence is considered as a systemic factor of economic effect, ensuring productivity growth, cost reduction, export expansion and strengthening of the tax base.

     In this model, the state apparatus is transformed into the state as a platform with a single data architecture that ensures compatibility and integration, as well as with a single space for decision-making and working with data. The consistent introduction of AI into government functions is accompanied by the optimization and redistribution of processes, institutional strengthening of data management, the formation of sustainable Data Governance mechanisms, and the development of project and operational offices for digital development.

     The modernization of the regulatory environment will be accompanied by the introduction of digital regulatory impact assessment, regulatory experimentation mechanisms, and accelerated procedures for adapting legislation to new digital models. Regulation will become predictable, transparent and focused on reducing the burden on businesses.

     Intelligent budgeting, monitoring, and data-driven strategy management ensure manageability, accountability, and measurable results. As a result, an adaptive, technologically mature and human-oriented state is being formed, capable of developing sustainably in the face of accelerating technological and socio-economic changes.

     The implementation of the Digital Qazaqstan Strategy is based on an ecosystem approach, in which digital development is considered as a coordinated and interconnected transformation of a person, economy and state apparatus. Digital technologies and AI are being implemented not in isolation by departments or industries, but as elements of a single national digital ecosystem, harmoniously united by common architectural principles, data, platforms and management mechanisms. The ecosystem approach involves synchronizing government policy, regulation, infrastructure, human resources, and technological solutions around common strategic goals. Special attention is paid to eliminating fragmentation, duplication and gaps between sectors and management levels, as well as ensuring the compatibility of digital solutions and data, and decommissioning duplicate solutions.

     The Strategy is being implemented through the development of the technological architecture of the country's digital development, in which each subsequent level builds on the previous one and ensures the large-scale implementation of digital solutions and AI technologies in all areas of the economy and public administration. The basic level is the energy infrastructure that ensures stable operation of data centers and high-load computing systems. The development of this level is carried out in synchronization with national energy development programs. The next levels are the formation of high-performance computing capacities and the development of a network of data centers. Having its own computing infrastructure will allow processing personal and government data on the national technological base within the country, ensuring their protection, strengthening the technological and digital sovereignty of the Republic of Kazakhstan. On this basis, the state's platform infrastructure is being formed, providing unified architectural standards for state information systems, scaling digital services, and integrating government and business solutions. The next level is the formation of the digital economy, which includes the introduction of unified national data management standards, the creation of industry-specific repositories and a national data infrastructure that ensures their quality, compatibility and security. The final level is the implementation of applied digital and AI solutions in key sectors of the state, economy and social sphere. At this level, industry-specific digital projects are being implemented, new services for citizens and businesses are being created, and the efficiency of public administration and the economy is being improved through the widespread use of intelligent technologies. Thus, an integrated architecture of Kazakhstan's digital transformation is being formed.

The main mechanism for the practical implementation of the ecosystem approach is the formation of a portfolio of icebreaker projects, which are used as the main format for resource concentration, coordination of participants and results management. National projects provide a transition from strategic goals to comprehensive packages of interrelated initiatives combining technological, organizational, regulatory and personnel changes. This format allows you to scale successful solutions, ensure interagency cooperation and focus on achieving measurable effects, build a step-by-step logic of change, ensure manageability of transformation and take into account differences in the level of digital maturity of industries and regions. National projects are becoming a mechanism for integrating digital and AI initiatives into key areas of the country's development, ensuring their consistency with the budget process, the state planning system and priorities of socio-economic policy.

     The cumulative economic effect of the Strategy is expressed in accelerating the basic trajectory of economic growth: due to the introduction of AI, digitalization of key industries, reduction of transaction costs and labor productivity growth, an additional contribution to GDP of about 1.5 percentage points per year on average is expected by the end of 2029 relative to the baseline scenario. The social effect is expressed in the state's transition to a proactive model of citizen support: reducing the time required to receive public services, increasing the targeting of social support, equalizing access to quality education and healthcare between urban and rural areas, and a preventive model of public health management. At the same time, technological sovereignty is being strengthened, and a stable export position is being formed in the segments of digital solutions and AI infrastructure.

     A complementary approach is the phased and adaptive implementation of the Strategy, which provides for the possibility of adjusting decisions as technological, economic and social conditions change. This allows us to take into account the dynamics of AI development, international practice and emerging risks, without violating the integrity and long-term logic of the Strategy.

     As a result, the Republic of Kazakhstan is forming a sustainable digital development model capable of providing technological leadership, economic competitiveness and strategic autonomy in a global AI economy.

     3.3. System integration of advanced world practices into the national ecosystem of artificial intelligence

     In the context of accelerating global competition in the field of AI, the sustainable development of the national AI ecosystem is determined not only by the availability of its own solutions, but also by the ability of the state to adapt and integrate advanced global practices in the field of infrastructure, data, regulation, personnel, scientific research, trust and technology scaling in a timely manner. International experience shows that leading states are building AI policy as an integrated system in which the development of computing infrastructure, human resources, implementation mechanisms, trust regulation and international technological cooperation is carried out in a coordinated manner. This is the approach that Singapore, the European Union, the United Kingdom, the Republic of Korea, Canada, the United States of America, and the United Arab Emirates are consistently implementing today.

     With this in mind, in the Republic of Kazakhstan on the basis of "Alem.AI" will form an institutional mechanism for the systemic integration of international AI development experience, ensuring continuous analysis, adaptation and implementation of world best practices in national digital development policy.

     This mechanism will be based on several interrelated areas.

     First, a strategic monitoring system for international AI development will be established. This system will provide regular analysis of national AI development strategies of leading technological states, as well as international technological trends, regulatory approaches and practices for the introduction of AI in economics and public administration. The results of this analysis will be used to update national AI development policies, adjust strategic priorities, and develop new initiatives.

     Secondly, a mechanism for technological transfer and integration of global competencies will be formed. It provides for the development of international research consortia, the creation of joint laboratories and development centers, as well as the involvement of the world's leading technology companies, universities and research organizations to implement projects in the Republic of Kazakhstan. Special attention will be paid to localization of technologies.

     Thirdly, a system of piloting and experimental implementation of advanced technological solutions will be created. For this purpose, the tools of the legal regime, regulatory "sandboxes" and special technological zones will be used to test new models of regulation and application of AI technologies in a controlled environment.

     Fourth, the integration of the Republic of Kazakhstan into international initiatives and platforms for cooperation in the field of AI will be ensured. Kazakhstan will actively participate in international research and technology partnerships, expert communities, and initiatives to develop international standards and principles for the responsible use of AI. This will ensure the compatibility of the national regulatory environment with international standards, increase the trust of international partners and strengthen the country's position in the global AI ecosystem.

     Fifth, a mechanism for the institutional dissemination of international practices within the country will be formed. Based on the analysis of the world's best solutions, standard digital platform architectures, data standards, AI implementation methodologies, and recommendations for government agencies, businesses, and the scientific community will be developed. This will ensure the systemic scalability of successful practices and reduce the risks of fragmentation of digital initiatives.

     The architectural coordination center under the authorized state body in the field of digitalization will play a central role in the implementation of this direction, ensuring constant monitoring of international experience, analysis of advanced technological and regulatory practices, as well as preparation of proposals for their adaptation and implementation into the national digital policy of the Republic of Kazakhstan.

     3.4. Strategic directions of implementation, ways of achievement, key performance indicators (CRI) and prospects

     Strategic direction 1. Digitalization and implementation of artificial intelligence in the interests of citizens

     As part of the Strategy, a new model of the digital state will be formed, with humans at the center as the driving force behind the development of human capital, knowledge, competencies, and innovation potential of the country. Digital transformation is considered not as the automation of individual services, but as the creation of an integrated system for supporting a citizen's life path from early childhood to active longevity based on data, analytics and AI technologies.

     The state will move from reactive service provision to proactive management of life trajectories. The use of integrated data will make it possible to identify educational, professional and social risks in a timely manner, form personalized support measures, and provide targeted solutions without excessive procedures and repeated collection of information. Citizen's interaction with the state will become "seamless", predictable and based on trust, where most services are provided automatically at the moment of need.

     A single digital contour of human capital will be formed, combining education, the labor market, healthcare, social and legal protection into an end-to-end data architecture. This will ensure the continuity of competence development, a transparent link between training and employment, as well as support for citizens at all stages of the life cycle.

     The education system will be transformed into a mechanism for the advanced formation of skills in the economy of the future, focused on individual educational trajectories, the development of digital and entrepreneurial competencies.

     The labor market will function as a dynamic ecosystem of continuous retraining and professional mobility, supported by digital tools for analyzing the supply and demand of competencies. Healthcare and social policy will shift to a preventive model based on early detection of risks, targeted support and reduction of inequality of opportunities.

     Human capital is considered as a key strategic resource of the country. Investments in its development will become a factor in the growth of labor productivity, innovation activity and long-term competitiveness of the Republic of Kazakhstan. A human-centered and inclusive digital society will be formed, in which equal access to development opportunities is ensured regardless of place of residence, social status or income level.

     As a result, the state will become a strategic partner of the citizen, providing not only access to services, but also conditions for unlocking the potential of each person as the main driver of sustainable economic growth and national development.

     Human capital development and the system of continuous competence formation

     The education system will be transformed from a knowledge transfer model into a platform for advanced competence formation for the data economy and AI. Education will be built as a continuous digital contour of human development throughout his life from preschool age to completion of professional activity using personalized learning trajectories and AI analytics tools.

Within the framework of the national AI education architecture and the AI-SANA program, a basic level of digital and AI literacy will be provided for each student and teacher. By 2028, at least 80% of graduates of general secondary, technical, vocational, and higher education institutions will have basic AI competencies, while at least 20% of higher education graduates will receive advanced training in AI competencies and AI entrepreneurship.

     In order to form a sustainable system of training teachers in the field of AI, it is planned to introduce a tiered model of competence development, including basic, advanced and expert levels. The basic level is aimed at ensuring the digital literacy of teachers. By 2029, it is planned to ensure coverage of at least 80% of teachers. The advanced level is focused on the practical application of AI technologies in the educational process. By 2029, the proportion of teachers with advanced competencies should be at least 25%. The expert level provides for the formation of a pool of leading teachers who provide methodological support and training for other teachers. By 2029, it is planned to form an expert community of 5% of the total number of teachers.

     The personalization of educational routes will allow taking into account the abilities, interests and professional goals, forming a flexible training model for the real needs of the economy. At the same time, practice-oriented training will be scaled up, enhancing involvement in engineering, technological and entrepreneurial areas.

     As part of the transformation of the higher and postgraduate education system, the introduction of modern digital approaches to the management of educational and scientific activities will be ensured, including the introduction of a digital rating of higher and postgraduate education organizations.

     At the same time, an end-to-end digital science management system will be implemented, providing for automated monitoring of scientific and scientific-technical projects to ensure transparency of budget spending.

     Higher education and scientific activity will be integrated into a single digital environment of the knowledge economy. Engineering universities will become centers of applied AI development and robotics, working closely with industry companies, government agencies and research consortia. AI University will develop as a national platform for training AI personnel, conducting research and replicating technological solutions. Robotics laboratories and a material and technical base for a full cycle of prototyping will be formed on the basis of regional universities. Educational programs will be adapted to modern requirements with the involvement of teaching staff with modern knowledge and competencies. The enrollment of students in technical specialties related to robotics will be increased. The coverage of schools with STEM classrooms and robotics circles will increase. The Astana Hub Autonomous Cluster Fund will create and support educational tracks for advanced training and retraining in IT and robotics, acceleration programs, and programs to support and stimulate startups in IT and robotics. At least 80% of universities will introduce AI into educational processes. The introduction of robotics by small and medium-sized businesses will be stimulated through the development of affordable technological solutions, service models and government support tools aimed at increasing productivity, reducing costs and accelerating the digital transformation of the economy.

     To this end, the AI-SANA program will become a backbone national mechanism for cooperation between education, science and business to create scalable IT products with high export potential and a separate focus on practice-oriented tracks in the most popular scenarios, so that training can be directly converted into increased work efficiency, service quality and accelerated diffusion of generative AI at the national level. countries.

     The labor market will be transformed into an intelligent human capital management system. A single contour of forecasting personnel needs will be formed, integrating macroeconomic indicators, industry development plans, demographic trends and business signals about the demand for competencies. Based on analytical forecasts, at least 80% of educational programs and target sets will be updated in accordance with the projected needs of the economy, ensuring the synchronization of personnel training with the strategic priorities of the country's development.

     Tools for matching skills and market requirements will provide a direct link between the education system and employment, allowing citizens to plan career paths, retrain without a gap in employment, and adapt to changes in the technological environment. Platform-based forms of employment and new work models will be integrated into a single labor market contour while maintaining social guarantees and income transparency.

     Diffusion of generative AI. As part of the Strategy, human capital development will focus on accelerating the practical development of generative AI as a mass skill and a basic tool for improving labor productivity and service quality. For this purpose, the diffusion rate of generative AI in the amount of at least 20%, reaching a level not lower than the global average at the time of assessment, will be fixed as one of the key measurable factors of the effectiveness of human capital policy. Measures will also be provided to accelerate the spread of generative AI, including the formation of sustainable user practices and the involvement of broad groups of the population. For this purpose, a transition will be made from disparate educational activities to a systematic learning model based on scalable tools: online courses, regional training centers and standard programs for different target groups, as well as the introduction of a system of target indicators.

     As a result, a managed ecosystem of human capital development will be formed, providing the economy with qualified personnel, citizens with clear navigation of opportunities throughout their lives, and the state as a tool for forecasting and shaping competencies for the country's strategic priorities. Human capital will become the foundation for productivity growth and long-term competitiveness of Kazakhstan.

     The implementation of these transformations will ensure the formation of human capital as one of the key sources of labor productivity growth in the transformed sectors of the economy.

     Unified digital Health Management System

     As part of the Strategy, the healthcare system of the Republic of Kazakhstan will be consistently transformed from a fragmented model of medical services into an integrated digital health management system based on data, analytics and AI technologies. The strategic goal of the transformation is to move from predominantly reactive treatment to proactive risk management, improve the quality of clinical outcomes, and ensure the long-term financial sustainability of the industry.

     A key element of the transformation will be the development of a technological health platform as part of the end-to-end digital architecture of citizens' life paths. The platform will integrate prevention, primary health care, diagnostics, inpatient treatment, drug provision, rehabilitation and long-term support into a single managed loop. The model will be based on a single digital profile of a citizen's health, integrating medical history, laboratory and instrumental research results, appointments, medical examination data and remote monitoring. This will ensure the continuity of clinical routes and the access of medical professionals at all levels to complete and up-to-date information about the patient, regardless of the region of care. By 2029, at least 20% of the population will use self-service medical services, and at least 95% of medical organizations will be integrated into a single digital circuit providing inter-level data exchange in real time.

     Primary health care will be strengthened as a central link for early disease detection and risk management. Based on data analytics and AI algorithms, digital stratification of the population by risk levels will be implemented with the formation of personalized preventive routes. Screening and follow-up will be prioritized among citizens who are more likely to develop complications. This will reduce the proportion of late diagnosis of socially significant diseases, reduce the number of emergency hospitalizations and increase the efficiency of using primary care resources.

     Diagnostic advisory services and telemedicine services will be integrated into unified digital clinical routes. Doctors will have access to a holistic digital patient profile, and clinical decision support tools will be used to analyze research results, form recommendations, and optimally route patients between levels of care. This will ensure improved diagnostic accuracy and more equal access to specialized medical expertise, regardless of the territory of residence.

Primary health care will be strengthened as a central link for early disease detection and risk management. Based on data analytics and AI algorithms, digital stratification of the population by risk levels will be implemented with the formation of personalized preventive routes. Screening and follow-up will be prioritized among citizens who are more likely to develop complications. This will reduce the proportion of late diagnosis of socially significant diseases, reduce the number of emergency hospitalizations and increase the efficiency of using primary care resources.

     Diagnostic advisory services and telemedicine services will be integrated into unified digital clinical routes. Doctors will have access to a holistic digital patient profile, and clinical decision support tools will be used to analyze research results, form recommendations, and optimally route patients between levels of care. This will ensure improved diagnostic accuracy and more equal access to specialized medical expertise, regardless of the territory of residence.

     Inpatient care will be focused on achieving measurable clinical outcomes. It is planned to introduce tools for predicting complications, optimizing indications for hospitalization and reducing the length of hospital stay, ensuring the transition to a more efficient healthcare model in which at least 80% of clinical decisions are made using AI technologies. Hospitals will be integrated into a single digital healthcare circuit, which will ensure continuity of treatment and more rational use of the bed stock.

     Laboratory diagnostics, visual examinations, drug provision and medical logistics will be combined into a single platform with the ability to use predictive analytics. This will ensure transparency of prescriptions and supplies, improve demand forecasting, and reduce the risks of drug shortages, including in the regions.

     Rehabilitation and post-hospital support of patients will be complemented by digital remote monitoring tools, which will ensure continuous monitoring of patients with chronic diseases and reduce the likelihood of re-hospitalization. The medical system will be built around the full life cycle of the patient, rather than individual episodes of care.

     The healthcare financing model will be gradually transformed from payment for the volume of services provided to payment elements based on clinical outcomes and public health indicators. End-to-end analytics will allow an objective assessment of the effectiveness of prevention, treatment and rehabilitation, forming the basis for improving the quality of medical care while reducing the long-term budget burden.

     Drug provision will be integrated into a single digital healthcare system covering the full life cycle of medicines, from demand planning and procurement to prescribing, dispensing and monitoring therapy. AI algorithms and predictive analytics will provide demand forecasting, reduce shortage risks, and optimize inventory. Digitalization of prescribing and dispensing processes will increase the transparency of drug therapy, control compliance with clinical protocols, and patient safety. The processes of storage and transportation of medicines will be further enhanced through digital monitoring and control solutions. Ensuring continuous monitoring of storage and logistics parameters in real time will improve the safety of medicines, reduce losses, and increase the efficiency of planning and using the resources of the drug supply system. Thus, a stable, transparent and analytically managed system of drug provision will be formed, aimed at increasing the availability, quality and efficiency of the use of budgetary funds.

     A modern and sustainable environment for life and development

     As part of the Strategy, a national digital living environment will be created as a unified real-time management system for the Territory. The living environment is considered as an integrated ecosystem based on AI, combining security, housing and communal infrastructure, transport, communications and services for citizens in a continuous loop of monitoring, analytics and preventive response.

     The architecture will be based on the principle of a single national data standard, common integration protocols and centralized analytics while maintaining the operational autonomy of the regions. The model tested in the capital will be scaled to all regions as a standard for digital infrastructure. By 2029, at least 70% of the urban population will live in regions that have implemented the basic components of the "Smart City" ("Smart Region").

     Public safety will be transferred to a preventive risk management model. The integration of video monitoring, remote detection of offenses, and behavioral analytics will ensure objective incident detection, threat prediction, and digital prevention. The implementation of the measures will reduce the response time to incidents by at least 10% and ensure a steady reduction in street crime in coverage areas by at least 10%. At the same time, a national system for protecting citizens from online fraud based on transactional analytics and proactive information will be formed.

     The housing and communal infrastructure will be switched to predictive management mode by creating a single digital data platform that will combine data from metering devices, utilities and government systems. A unified register of facilities with digital passports and intelligent metering devices will create a transparent operating model. Artificial intelligence and IoT will ensure early detection of anomalies, optimization of resource consumption and repair planning.

     Urban mobility will function as an intelligent transportation system synchronized with emergency services and communal infrastructure. The use of AI monitoring platforms will reduce congestion in large cities by 20-25% and increase compliance with public transport schedules by up to 90%.

     All data on transport, housing and communal services, security, and citizens' appeals will be integrated into a single national territory management platform and akimats' situation centers. An end-to-end digital chain "handling - dispatching - elimination - confirmation - analytics" will be provided, forming a controlled operational cycle of the urban environment.

     Digital connectivity will become the basic infrastructure of the environment of life, economy and security. As part of the strategy and existing initiatives in the field of digitalization, a single national IT circuit is being formed, combining fixed, mobile and satellite networks. High-speed Internet is being expanded in rural settlements (hereinafter referred to as SNPs) with coverage reaching 92% and connecting more than 3,000 SNPs in 2025-2027, continuous digital coverage is being created along more than 40,000 km of highways, in tourist locations and border areas. The mobile infrastructure is switching to 4G as the basic standard with a connection of more than 5,900 SNPs. 5G is scaled in more than 20 cities for industrial and AI scenarios. Satellite communications are being deployed for remote areas, trains and aviation, as well as for the development of Kazakhstan's digital transit potential, fiber-optic communication lines are being built along the bottom of the Caspian Sea. Communication is used as a base layer for video monitoring, sensor systems, unmanned solutions, and operational data exchange.

     The development of digital connectivity is accompanied by measures to ensure the accessibility of adapting services to different age groups and levels of digital skills. All elements of the living environment will be integrated into a scalable "Smart Region" architecture. Akimats will receive digital control panels based on a single data model and standardized performance indicators.

     As a result, a sustainable, secure and manageable digital living environment will be created, comparable in quality standards to leading global agglomerations. The system will ensure risk prevention, reduce transaction costs, increase the investment attractiveness of territories and increase the satisfaction of citizens.

     Data-based public services and targeted social support

     Public services will cease to be a set of disparate departmental procedures and will be transformed into unified digital scenarios that accompany people in life situations without the need for multiple requests, providing certificates and re-entering information.

     A new model of citizen-state interaction will be formed, based on life events, data, and AI technologies, ensuring the simplicity, speed, and clarity of receiving services. A unified digital citizen profile and a "life track" will be developed. Based on them, the state will switch to a model of needs recognition and non-explicit provision of services, in which a significant part of decisions will be made automatically upon the occurrence of specified conditions, and the citizen will receive support without submitting applications. It is planned to transform at least 40% of public services through the introduction of AI technologies, transfer to a proactive format, as well as the introduction of automatic signing and process automation mechanisms.

Life situations will be implemented as end-to-end end-to-end scenarios in a single digital window, in which the system will independently collect the necessary data from state registers, form a package of services and accompany the citizen until the result is achieved. Government services will be result-oriented rather than procedure-oriented with a focus on speed of delivery, completeness of life situation solutions and reduction of administrative burden.

     Social support will be transformed into an intelligent "smart targeting" system. AI technologies will be used to identify life risks, predict social vulnerability, and provide targeted assistance. Payments and benefits will be assigned automatically upon the occurrence of appropriate conditions, and if the life situation changes, the system will adjust the amount and format of support without the participation of a citizen. This will ensure the transition from a declarative model to a predictive social policy, reduce the proportion of erroneous and excessive payments, and ensure the concentration of resources on really needy categories of the population.

     The principle of completely eliminating the use of scanned copies of documents and paper certificates will be implemented. Management and service decisions will be made based on verified data, rather than documents provided by a citizen. Public service centers will be transformed into digital public offices focused on supporting difficult life situations and unusual cases, rather than accepting applications.

     The e-Finish platform will be used as a source of continuous improvement of government services. The processes of identifying problem areas, hidden services, and ineffective scenarios will be automated, and the quality of decisions made will be assessed based on actual life outcomes for citizens.

     As a result, the development of a unified digital platform for government interaction with citizens will be ensured, providing end-to-end scenarios of life situations, reducing the proportion of erroneous social assignments and providing public services without using scanned copies of documents and paper certificates. The average time for the provision of public services and social support measures is planned to be reduced by at least 50%. The state will switch to an AI-based model of citizen support, reducing access barriers, increasing targeted support and forming a sustainable social protection system.

     The types of socially significant services will be expanded, covering all spheres of society. The introduction of AI technologies will improve the quality of socially significant services, predict possible risks, identify problem areas and respond promptly, as well as analyze the needs of the population.

     Strategic direction 2. Digitalization and the introduction of artificial intelligence in the interests of business and the economy

     In the context of the accelerating global technological transition, the digital transformation of the economy will be aimed at increasing productivity, diversifying sources of growth and creating new added value. Digitalization is considered as a tool for the systemic modernization of the country's economic model.

     The strategy will be based on the principle of focused transformation: digital and AI tools are prioritized for scaling in sectors that account for the bulk of GDP, export potential, and employment. This approach ensures the concentration of resources in areas with maximum multiplicative effect and the transition from fragmented automation to a controlled increase in labor productivity.

     The perimeter of the transformation will include the removal of systemic barriers to business development, including lengthy licensing procedures, high administrative burden, and limited access to data, infrastructure, and government support measures.

     The transformation will be implemented through industry-wide digital modernization of key sectors of the economy, the introduction of mandatory data standards and their interoperability, the integration of AI platforms at backbone enterprises, the development of industrial digital twins, as well as strengthening technological sovereignty through the priority implementation of domestic solutions and localization of critical technologies.

     Small and medium-sized businesses will be integrated into the national digital ecosystem as a key source of employment and economic growth. Unified digital support loops will be created to provide access to finance, data, digital services, and AI tools to improve efficiency.

     At the same time, the modernization of the real sector will become a stable domestic market for the national IT sector and the startup ecosystem, generating demand for domestic digital solutions and creating conditions for their scaling and export.

     A separate strategic direction will be the development of the new digital economy as an independent sector based on national computing infrastructure, cloud and hardware capacities, applied AI products and the export of technological solutions.

     The digital economy will become a driver of the country's investment attractiveness, reducing transaction costs, increasing the competitiveness of national businesses and strengthening its position in the global technology market.

     Digital transformation of key industries

     The role of the state in the digital transformation of industries will be fundamentally changed. Its function will be to form unified data standards and architecture, create regulatory and tax incentives, provide access to digital and computing infrastructure, and generate scalable demand from the economy. The implementation of digital and AI solutions will be carried out by the business itself and the technology market.

     At the same time, industry-specific digital circuits will be formed in key industries, including situational centers, at least 10 specialized data warehouses ("data lake"), functioning according to uniform requirements for data quality, structure and compatibility. Work will also continue on the high-quality content of national registers. Digitalization of state statistics will become an important element of the data management system. It provides for the expansion of the use of administrative and alternative data sources, as well as Big Data technologies, improving the quality and relevance of statistical information, and developing verification and interdepartmental reconciliation mechanisms. This will improve the efficiency of decision-making, reduce duplication of reporting, and strengthen the analytical framework of public policy. On this basis, end-to-end monitoring of the state of industries, production indicators, logistics, investments and risks will be provided, as well as predictive analytics will be introduced to identify bottlenecks, predict dynamics and support management decisions. This model will ensure the transition from fragmented control to managing the development of industries based on data and AI while maintaining the leading role of business in the implementation of digital solutions.

     A unified national digital contour for managing the country's resource base will be formed in the oil and gas sector and subsurface use. An end-to-end "subsoil - mining - transportation - processing - export" architecture will be built, within which geological data, production indicators, production accounting, environmental monitoring and fiscal information will be combined into a single digital environment. Instrument accounting of production, movement of hydrocarbons and solid minerals at all stages of the production chain will be scaled up, IoT sensors and digital field passports will be introduced. Based on AI technologies, reserves forecasting, modeling of development scenarios, optimization of production and transportation modes, as well as predictive management of technological and environmental risks will be implemented. The state will receive tools for proactive resource base management, which will increase the transparency of the industry, the accuracy of tax administration and the investment attractiveness of subsurface use. By 2029, it is planned to cover at least 70% of the key assets of the fuel and energy complex with AI monitoring and management systems. As part of the development of digitalization and the use of AI to manage the mineral base, there is a potential for private investment in exploration to increase by at least 30%.

     In the context of the active development of data centers, AI clusters and the active introduction of AI, the energy system is becoming a strategic infrastructure for national development. There will be a transition to an intelligent energy system operating on the basis of a unified digital architecture and predictive control. A digital twin of the national energy system will be created, covering generation, networks, balancing and key industrial nodes, providing real-time simulation of development scenarios. The energy system will switch from reactive management to forecast-based management, which will reduce technological losses, reduce accidents, increase supply reliability and ensure predictability of investment decisions. AI will be integrated into strategic planning, demand forecasting, dispatch management, and asset management. Special priority will be given to ensuring the flexibility of the energy system with an increasing share of renewable sources and distributed generation, as well as creating an energy base for the digital economy, including data centers and industrial parks. Cyber resilience of the energy sector will be built as part of the national security architecture using AI systems for early threat detection and segmentation of critical infrastructure.

The industrial sector will move from disparate automated sites to the formation of a national industrial digital circuit. Data on capacity utilization, downtime, product quality, energy consumption, and equipment technical condition will be combined into an industry-specific "data lake" and reflected in national registers. Industrial IoT, MESS systems, ERP systems (enterprise resource management systems), which ensure the integration of production processes with planning, supply, repairs and management accounting, as well as digital counterparts of production lines, will become more widespread and integrated in enterprises. Artificial intelligence will be used for predictive asset maintenance, optimization of production cycles, quality management and reduction of raw material losses. This will reduce unplanned downtime, increase equipment utilization, and reduce production costs. A transparent picture of the state of the industry will be created for the government and investors, simplifying investment decision-making and supporting industrial modernization. By 2029, it is planned to introduce digital twins in at least 60% of large industrial enterprises.

     The implementation of ERP systems will be stimulated, ensuring the integration of finance, production, logistics and personnel management in a single digital environment, which will create the basis for the introduction of artificial intelligence and data analysis technologies.

     The transport and logistics sector will be transformed into a national-scale managed digital system based on the principle of "time economy instead of distance economy". A unified digital transit and cargo transportation system will be formed, ensuring full accounting of the country's transport assets, including automobile, railway, river, marine and aviation parks, infrastructure, terminals, warehouses and transport corridors. National and international integrated cargo tracking platforms will be developed, combining electronic documents, licenses, permits, customs, border, sanitary and phytosanitary procedures into a single digital process. A unified intelligent transport system will be implemented, consolidating existing information systems and digital solutions, forming a reference industry "data lake". An intelligent tool will be created for the state to conduct predictive analytics, have up-to-date information on the current situation in the entire transport industry and make high-quality, timely decisions. All stages of transit from sender to recipient will ensure seamless passage of borders, terminals and checkpoints without separate departmental procedures. Along with measures to diversify transport corridors, full traceability of routes, infrastructure utilization and corridor capacity will be ensured. AI will be used to plan multimodal routes, predict bottlenecks, optimize customs clearance, and manage flows, which will reduce downtime, increase predictability of delivery times, reduce costs, and maximize the use of transportation capacity. Logistics will be integrated with the industrial, agricultural and financial contours of the economy, forming a digital framework for sustainable supply chains, increasing transit potential and strengthening the role of the Republic of Kazakhstan as a key transport hub. By 2029, it is planned to ensure at least 80% cargo tracking, a complete transition to electronic document management in the field of transport and logistics, as well as a reduction in the average border crossing time by at least 8 times (from the current 4 hours).

     The financial sector will be transformed into a proactive and data-driven system. Special attention will be paid to the implementation of graph analytics-based solutions and multi-agent models for the automated detection of abnormal transactions, transit schemes and related counterparties. In parallel, a national anti-fraud circuit will be formed with the integration of banking, telecommunications and government segments, providing predictive detection of fraud and illegal payment transactions. The digital tenge is not only a digital form of the national currency, but also a component of the national digital financial infrastructure integrated into the sectoral contours of the economy and public administration. The digital tenge can serve as a tool to increase the transparency of financial flows.

     The digital tenge will become the basic platform for the implementation of smart contract mechanisms that automate the fulfillment of government obligations, subsidies, transfers and targeted financing. This will create conditions for the transition from after-the-fact control to integrated management and monitoring of the targeted use of funds, including budget programs, social support, infrastructure projects and public procurement. The integration of digital tenge with industry platforms will allow for the formation of end-to-end digital financial and operational contours. The financial system will be complemented by an open digital architecture that integrates banking and non-banking services, including insurance, leasing, factoring, export financing and alternative payment solutions, into a single support loop for investment and production projects. A model will be developed in which financial products will become an integrated part of industry and digital platforms, providing enterprises with access to finance directly within the framework of operational activities. Special attention will be paid to the development of the non-banking fintech segment as an independent source of growth through the scaling of digital insurance, factoring, equipment leasing, export financing and alternative investment platforms. This will ensure the diversification of the financial ecosystem, expand the access of small and medium-sized businesses to capital, and form sustainable financial chains around industry, agriculture, and logistics.

     In support of these initiatives, considerable attention is being paid to the further development of non-bank payment service providers, which will diversify available payment services and promote competition. As a result, Kazakhstan will move to a new stage of development as an international fintech hub.

     The construction industry is transforming from a fragmented system of approvals and disparate projects into a single digital ecosystem for managing the life cycle of facilities from territory planning and design to construction, commissioning and subsequent asset management. A national digital construction platform will be developed, combining data on land plots, urban planning regulations, engineering infrastructure, project documentation and the actual progress of construction. It is planned to introduce SIM models and digital counterparts of buildings, providing end-to-end maintenance of facilities and the transition from a document-based approach to data-based management. By 2029, it is planned to ensure 100% of the implementation of VIM technologies in the design of new facilities and 100% of instrumentation and digital monitoring in the housing and communal services sector in cities of national significance and regional centers.

     All licensing and approval procedures will be digitized with transparent tracking of deadlines and statuses. AI will be used for automated analysis of project documentation, identification of non-compliance with regulatory requirements, resource planning and monitoring of construction work. This will shorten the project implementation time, reduce transaction costs, minimize corruption risks, and increase the predictability of investment processes. The industry will be integrated with the financial sector and infrastructure circuits, providing end-to-end project support from obtaining permits to financing and connecting to utility networks. As a result, construction will become a managed digital system that increases the pace of housing and infrastructure commissioning, the quality of the urban environment and the investment attractiveness of the territories.

The agro-industrial complex will be transformed through the formation of a unified national digital ecosystem that ensures the transition from disparate industry administration to data-based, AI-based, and end-to-end digital traceability agriculture management. This ecosystem will become a digital operating system of the agricultural sector, combining government services, production data, financial instruments and export mechanisms into a single platform contour. The industry will move from fragmented solutions to an integrated management model based on the principle of "data - forecast - solution - result", ensuring increased efficiency, transparency and competitiveness of the agricultural economy. A single industry-wide "data lake" will be created, combining data on land resources, acreage, weather conditions, agrochemical characteristics of soils, state of technology, livestock, yields, subsidies and logistics. On this basis, the transition to digital profiles of farms and the management of state support based on actual productivity and resource efficiency will be ensured. Precision farming, satellite monitoring, IoT sensors, biometric control in animal husbandry, and AI yield forecasting will become the industry standard. Production decisions will be made based on analytics, not intuition. Government support will be integrated into the digital circuit and provided in a "one-stop shop" format with full transparency and traceability. An end–to-end digital land-production-storage- processing-logistics-export chain will be created to ensure product traceability and compliance with international quality standards. This will make it possible to move from a raw material model to a controlled increase in added value and processing within the country. The government will move from subsidies to results management: support will be linked to digital indicators of productivity, efficiency and resilience to climate risks. Innovative solutions and smart farms will receive priority support. By 2029, it is envisaged that the gross output of subsidy recipients will increase by 3-5% relative to the control group of comparable farms in the same region.

     The role of SMEs will be transformed from an object of regulation into an active participant in the national digital economy. A single digital support loop will be formed for entrepreneurs, combining access to finance, insurance, subsidies, export services and industry platforms. AI will be used to assess the sustainability of companies, predict demand, and identify bottlenecks in supply chains, providing targeted support and the formation of sustainable regional business ecosystems. As a result, small and medium-sized businesses will receive a predictable digital environment "eGov Business" for growth, and the state will provide a managed business development contour that turns SMEs into a systemic factor of employment, competition and economic diversification.

     An intelligent model of tax administration

     Tax administration will be transformed from a primarily control mechanism into an intelligent service platform for monitoring economic activity, covering the entire business lifecycle - from registration and initial operations to scaling and entering export markets. The government will move from reactive control to a model of "invisible" tax administration based on AI data and technologies, in which tax liabilities will be calculated automatically, key risks will be identified proactively, and bona fide businesses will be freed from excessive checks and manual procedures.

     A single digital tax office will be created for entrepreneurs with real-time billing, transparent display of tax obligations, payments made and available benefits, as well as proactive notifications and recommendations. The tax system will serve as an economic navigator, offering financial support measures, industry development programs, and financial planning tools based on the company's digital profile.

     Invisible tax administration will become a new pillar of fiscal policy based on a differentiated model reflecting the real structure of the modern economy and the peculiarities of value creation in different segments. This approach will make it possible to abandon universal and redundant administration in favor of fine-tuning the tax contour. This will create conditions for the formation of tax obligations based on relevant digital data for each segment of the economy, increasing the collection, fairness and sustainability of the budget system.

     AI technologies will be used for predictive turnover analytics, identification of risky transactions, forecasting tax revenues and modeling economic effects, which will link fiscal policy with the goals of industrial, investment and regional development.

     The tax contour will be iterated with industry-specific digital platforms, subsidy systems, export support tools and financial institutions, forming a unified architecture of interaction between the state and the economy. In this model, the tax system will serve as a sensor of economic activity, providing the state with operational data on business dynamics, investment activity and structural changes in the economy.

     As a result, a "taxes as a service" model will be formed, within which tax administration will function in the background for a bona fide business and will reduce transaction costs, as well as increase trust and accelerate investment decision-making, providing entrepreneurs with a predictable and transparent development environment, and the state with a tool for intelligent economic management.

     By 2029, it is planned to reduce the shadow economy from 16.71% 23 (official statistics for 2024) to 13.8%24. As a result of the reengineering of government processes, B2B and B2G interactions will be digitized, the share of traceable turnover (categories) will grow to 50%, automatic calculation and pre-fulfillment of at least 80% of tax obligations of SMEs will be provided, the number of inspections of bona fide taxpayers will be reduced by at least 50% due to a risk-based approach, and It also reduces the time required to administer tax procedures by at least 50%. At the same time, the accuracy of forecasting tax revenues based on AI models will be improved and the proportion of disputed charges will be reduced. As a result, small and medium-sized businesses will receive a predictable digital environment.

     _____________________________________

     23https://stat.gov.kz/ru/industries/economy/national-accounts/publications/427384/

     24 In accordance with the Concept of Development of small and medium-sized enterprises in the Republic of Kazakhstan until 2030, approved by the Decree of the Government of the Republic of Kazakhstan dated April 27, 2022

     The financial sector

     To ensure the sustainability, security and competitiveness of the financial sector, digital transformation will focus on building a holistic digital financial architecture. Its development will focus on creating a trusted, data-driven, and technologically resilient environment in which payment infrastructure, regulation, cyber defense, anti-fraud circuits, and digital asset turnover evolve as interconnected elements of a single system.

     As part of the strategic direction, a modern digital financial infrastructure will be created that provides fast, reliable and secure 24/7 payments, inter-system compatibility, payment sovereignty and convenience for citizens and businesses. National payment circuits will become the basic technological "rails" for scaling new payment scenarios, open integrations, digital service channels and innovative financial services. In order to increase the cyber resilience of the financial sector in the context of global digital transformation, it is planned to implement a number of cybersecurity initiatives, including the development of a unified technology platform for financial sector regulators and the formation of a cyber polygon as part of the development of financial sector information security.

     The key basis for the development of the financial market will be the formation of a single secure financial data space in which data is considered as a managed asset, and decision-making is based on advanced analytics and AI tools. This model involves the introduction of a modern data management platform with transparent data origin, unified reference books, quality control, and the ability to quickly exchange data between market participants and regulators. This will create conditions for the transition to smart supervision and regulation based on data, early detection of risks, proactive rationing and reducing the regulatory burden on bona fide market participants.

     A separate area will be the creation of a secure contour for the development of digital financial services. Anti-fraud measures, cybersecurity and centralized risk monitoring will be aimed not only at reducing losses and eliminating vulnerabilities, but also at creating a secure "corridor" for scaling digital payments, online lending, tokenization and other innovative models. The fight against fraud and cyber threats will be built as a single predictive threat management system at the level of the entire financial market using common standards, analytical platforms and rapid response mechanisms.

The development of tokenization and the digital asset industry will ensure the formation of a transparent and reliable ecosystem for the issuance, circulation and accounting of digital assets with clear rules, secure infrastructure and traceability of transactions. This will make it possible to use digital assets as a new tool for attracting investments, increasing transparency and expanding the financial capabilities of the real sector of the economy.

     Development of a competitive IT industry

     The IT industry is transforming into a full-fledged technology industry embedded in the overall transformation of the economy and focused on creating scalable products, industry platforms and exporting technological solutions.

     The government will shift its role from direct participation in the development of digital solutions to the formation of sustainable and predictable demand, uniform architectural standards and conditions for scaling private market products. Internal developments, with the exception of solutions that ensure the implementation of specific sectoral (or supervisory) functions of the state apparatus, will be phased out. Priority will be given to domestic IT companies and startups through transparent piloting, replication, and long-term contracts.

     The introduction of guaranteed demand mechanisms and offtake contracts will ensure the formation of a predictable product-implementation-scaling investment cycle. The presence of proven demand from the government and the quasi-public sector will create a clear basis for financial institutions to lend to technology companies, reduce investment risks and expand access to financing. Thus, the IT sector will become a full-fledged object of investment financing.

     At the same time, the national implementation market will be expanded: successful pilot solutions will receive guaranteed scaling when achieving measurable effects. This will bridge the gap between development and operation, create a steady demand for domestic solutions, and ensure the integration of the IT industry into the production chains of industry, energy, agriculture, and logistics.

     The IT product infrastructure will be developed, including national cloud solutions, computing and hardware capacities, an industry-wide "data lake" and model libraries, which will ensure the creation and scaling of AI solutions within the country without critical dependence on external platforms. In order to strengthen technological sovereignty and develop the national AI ecosystem, special attention will be paid to the development of digital services and technologies for the Kazakh language, including the formation of a national corpus of Kazakh-language data.

     In parallel, an ecosystem of venture financing, development institutions, the banking sector and private capital will be formed, covering the entire life cycle of technology companies from the early stages to entering international markets. Based on the assessment of the risk profile of the relevant projects, financial institutions are gradually involved in venture financing of technology companies, and support tools are shifting from grant models to co-investment, repayment mechanisms and industrial partnerships focused on scalable products and sustainable growth.

     It is planned to create a balanced model for the development of mature IT companies and startups with transparent digital support, financing and cooperation mechanisms, as well as to provide systematic support for the entry of Kazakhstani IT companies into international markets through financial, diplomatic and infrastructural mechanisms.

     Considering that up to 70-80% of software development costs are paid for by highly qualified specialists, the expansion of the domestic implementation market will lead to a direct increase in household incomes, the formation of high-performance employment and an increase in the tax base. Thus, the IT industry will become one of the drivers of the growth of human capital and the digital economy.

     By 2029, it is planned to ensure an increase in the volume of exports of IT services and digital solutions by at least 2 times compared to the level of 2024, as well as the formation of at least 3 unicorn-level technology companies.

     The expansion of export potential and the growth of the domestic market will become the basis for the creation of at least 20,000 new jobs in the high-tech and digital sectors, including software development, AI, data analysis and digital services.

     As a result, Kazakhstan will form a competitive national IT industry with strong product companies, a developed startup ecosystem and a stable implementation market. The IT sector will subsequently become a driver of productivity growth, technological sovereignty, and economic diversification.

     Formation of a new economy

     The strategy plans to lay the foundation for a new economy based on the development of computing infrastructure, AI clusters and experimental technology zones, unmanned systems and autonomous mobility, digital assets and the crypto industry, space services and industrial robotics. These areas will form a new layer of added value, ensure the technological sovereignty of the country and become the basis for the creation of export-oriented industries of the future.

     The core of the new economy will be a national "AI Hub" focused on exporting computing power and AI services. It will be based on the "Valley of Data Centers", which provides access to hardware capacities and forms a full cycle of development, training and scaling of AI products by 2029 with a target power level of up to 200 MW, followed by an increase in maximum capacity to 1 GW. AI - Hub will develop as a regional competence center, attracting investments, international R&D teams and leading technology companies.

     In parallel, an ecosystem of the unmanned industry and autonomous mobility will be formed. It is planned to implement a pilot project of autonomous transport, which will make it possible to assess the safety and reliability of autonomous driving technologies in practice, and identify regulatory and infrastructural barriers. Within the framework of this direction, it is planned to improve legislation in terms of cybersecurity and responsibility, increase the efficiency of the transport system, as well as the phased integration of autonomous transport into the country's economy. As part of the development of urban air mobility, including the development of passenger (air taxi) and cargo unmanned transportation, flexible regulatory approaches will be introduced with a clear separation of requirements depending on the type of missions, the weight of unmanned systems and the degree of risk of operations performed. Thus, the foundations of a digital ecosystem of unmanned traffic management will be created for the introduction of unmanned vehicles and drones into urban, industrial and logistics infrastructure based on the principles of an open market with the involvement of private companies providing navigation services for drones.

     A separate focus will be the development of the crypto industry and the digital asset market as part of the country's financial and technological architecture. It will provide for the release of a stablecoin as a cryptographic gateway for digital commerce. The regulation of digital financial assets will be formed, including the tokenization of securities, goods and real estate, the development of a crypto exchange infrastructure and the launch of a national strategic crypto reserve. This will create conditions for attracting capital and developing new financial services. As a pilot jurisdiction for testing new regulatory models and technological solutions, a specialized regime is being formed within the framework of the development of Alatau City (CryptoCity) using an experimental legal regime.

     At the same time, high-tech areas of long-term growth will be laid. The national satellite program "Made in Qazaqstan" will be implemented, providing for the creation of an international grouping of domestic satellites and entry into the launch services market, which will ensure the development of its own orbital infrastructure and the export of space services.

     The creation of a robotics industry in Kazakhstan and the robotization of the economy will become separate strategic priorities. Over the next three years, an accelerated program for the formation of an export-oriented robotics industry will be implemented with the simplification of the legal regulation regime, the introduction of regulatory incentives, training, creation of laboratories and an ecosystem for the implementation of innovative initiatives. The industry's formation policy will include stimulating domestic developments both on a bottom-up basis through acceleration programs and open laboratories, and from top to bottom through the creation of an open target technology order and offtake contracts in priority sectors of the economy, including subsoil use, logistics, industry, healthcare, defense and agriculture.

     To finance the developments, a multi-channel venture financing system will be formed, and bank financing mechanisms will be worked out. Industry support mechanisms will be implemented at the stages from idea to industrial production and export, including patent, certification and export support. The promotion of exports of "Made in Qazaqstan" robotics products will become one of the priorities of foreign policy. To accelerate entry into global supply chains, targeted work will be carried out with world industry leaders to attract them to Kazakhstan, localize production and transfer export-oriented technologies.

To finance the developments, a multi-channel venture financing system will be formed, and bank financing mechanisms will be worked out. Industry support mechanisms will be implemented at the stages from idea to industrial production and export, including patent, certification and export support. The promotion of exports of "Made in Qazaqstan" robotics products will become one of the priorities of foreign policy. To accelerate entry into global supply chains, targeted work will be carried out with world industry leaders to attract them to Kazakhstan, localize production and transfer export-oriented technologies.

     By 2029, the new economy will provide: 1) the formation of a regional AI and digital infrastructure center with the involvement of large-scale private investments, the creation of a world-class national computing base, 2) the growth of exports of high-tech services, consolidating Kazakhstan's position as a key technology hub in Central Eurasia.

     Strategic direction 3. Digitalization and implementation of artificial intelligence in the state apparatus

     The Strategy will provide for a deep institutional restructuring of the public administration system aimed at moving from a departmental and functional model to a platform-based state based on AI, with at least a half reduction in the time of interdepartmental interaction.

     As part of the Strategy, the transition to paperless interaction will be ensured, in which decisions are made based on reliable data contained in government information systems, without the need for certificates and documents from citizens and businesses, and interagency cooperation (G2G) will be fully digitized with the exception of paper document management, duplicate requests and manual procedures. providing end-to-end data exchange and automated decision-making.

     With a significant number of administrative and interdepartmental procedures, digitalization will not be limited to automating existing processes. An assessment of the regulatory burden and the actual value of government procedures for citizens and their real contribution to socio-economic development will be carried out.

     As a result of the work, the processes will be reduced, consolidated and standardized. Government procedures will be transferred from departmental logic to end-to-end life and economic scenarios. Unified reference processes will be formed, which will later be implemented digitally on government platforms, and measures will be taken to unify methodology, bring various methods, approaches, and procedures to a single standard, form, or system that will aim to increase comparability of results, efficiency, and data manageability. This will create the basis for the implementation of AI agents that automate the adoption of standard decisions, support of appeals, control of execution and monitoring of results. The State apparatus will move from performing formal procedures to managing measurable socio-economic effects.

     The fragmented ecosystem of information systems will be replaced by a platform architecture. A phased migration to the domain model with the formation of industry-specific data warehouses will be implemented. To do this, an inventory and architectural audit of government information systems will be conducted to determine the target status for each system: development on the platform, consolidation, migration, decommissioning, and more. Requirements will be established to avoid duplication of functionality, reuse of platform components and data. Monolithic and outdated solutions will be decommissioned through centralized modernization, the transition to cloud infrastructure, and the creation of redundant computing circuits. As a result, a unified digital environment for government interaction with citizens and businesses will be created, ensuring the simplicity, speed, targeting and predictability of services.

     Given the scale of the required changes and the distributed IT landscape, the three-year horizon of the Strategy focuses on priority measures: eliminating critical sustainability risks, launching migration to the platform architecture, and reducing duplication. Complete modernization and replacement of outdated solutions are implemented in stages and require successive planning cycles beyond the first three-year stage.

     Full-fledged hot and cold backup centers for critical systems will be established. This will ensure the scalability of the digital environment, the readiness to implement AI models, and the sustainability of government services.

     Up to 30% of the operational workload of government employees will be transferred to AI solutions for handling complaints, preparing management decisions, monitoring execution, generating analytics and reporting. Managers will receive digital control panels with performance, risk, and program progress indicators. The role of the civil servant will shift from the document operator to the architect of processes and results.

     With the exponential development of technology, the current model of rulemaking and budget planning is no longer in line with the pace of the digital economy. New technological solutions will appear within days and weeks, while their legal consolidation and financial support within the framework of traditional procedures will take much longer. This gap between the speed of innovation and the speed of government response will be seen as one of the key institutional constraints of transformation.

     As part of the Strategy, the logic of the regulatory cycle will be revised with the transition to a more flexible, iterative model of regulating digital solutions, providing for consistent testing, fine-tuning and scaling of regulatory approaches. In this regard, it is assumed to rely on the regulatory testing regimes of innovations in Kazakhstan: the regulatory sandbox of the National Bank of the Republic of Kazakhstan and the FinTech Lab regime of the Astana International Financial Center, within their established competence and applicable legal regime, as well as reliance on the emerging specialized regime within the framework of the development of Alatau City (CryptoCity). Such mechanisms can be used to test individual digital solutions in a controlled environment and form the practice of their subsequent regulatory design. The logical continuation of this model will be a gradual transition to machine-readable law, in which regulatory requirements will initially be designed digitally and integrated into government platforms, which will ensure their automated application and significantly shorten the path from the adoption of legal acts to their practical implementation in the economy and public administration system. As a result, legal regulation will shift from an after-the-fact reaction to a proactive model in which the government will support the implementation of technologies in real time, promptly adapting requirements and removing barriers to scaling solutions.

     A similar transformation will be implemented in budgeting. Budget planning will be transformed from an inertial multi-month procedure into an adaptive change management tool. Mechanisms for the rapid reallocation of resources and financing of digital initiatives will be formed without waiting for standard approval cycles. Financial decisions will be linked to measurable effects, cost reductions, and productivity gains, rather than solely to formal items of expenditure.

     As a result, a single technology - law-budget chain will be formed, within which regulatory and financial mechanisms will be synchronized with the actual pace of digital transformation. This will accelerate the introduction of innovations, increase the return on public investment and ensure that the public administration system conforms to the dynamics of the modern economy.

     The state apparatus will gradually abandon its own product development. His key role will focus on shaping architecture, data standards, regulatory frameworks, and sustainable demand for digital solutions.

     To make the transition to a compact government based on AI, a sovereign data processing infrastructure will be formed, including government cloud solutions, hardware and computing clusters and secure storage. This will ensure local training of models, secure work with sensitive data, and large-scale implementation of AI in key management circuits, creating a technological basis for automating processes, reducing machine load, and increasing the speed of decision-making.

     Based on industry data from key sectors, a single "data lake" will be formed, integrated into the overall data management architecture. The repositories will be built as interconnected circuits providing end-to-end analytics and scenario modeling of socio-economic processes. Technological and methodological roles will be differentiated to ensure information security, data quality control, and interagency exchange. The authorized body in the field of state statistics will carry out methodological coordination of the data management system, including the formation of unified approaches, the maintenance of reference data and the definition of data quality assessment.

These approaches will form the basis of an architecture based on the "one source, multiple use" principle, which provides for a single collection of data and their subsequent application by government agencies for analytics, monitoring and decision-making. Special attention will be paid to the implementation of Data Governance practices and data quality assurance, including the development and implementation of a national data quality standard that establishes uniform quality requirements, as well as criteria for ensuring it: completeness, reliability, comparability, relevance, consistency and consistency of data in government information systems.

     At the same time, government agencies will introduce a standard methodology for the formation of metadata, covering the full cycle of data description, from their collection to subsequent use, and creating the basis for the transition to the formation of qualitative data characteristics. This ensures their comparability, reuse and integration, as well as a prerequisite for the development of analytics, the introduction of AI technologies and improving the efficiency of public administration based on data.

     As part of the development of the data economy, mechanisms for responsible exchange and turnover of digital data products between the government, business and the scientific community will be formed, ensuring the development of analytics, forecasting industry development, evaluating the effectiveness of decisions made, as well as the creation of new digital services.

     A national cybersecurity circuit of the state apparatus will be formed, covering government agencies, the quasi-public sector, and organizations connected to government digital platforms and data circuits. Given the transition to unified platform solutions and industry-specific data contours, cybersecurity is being consolidated as an absolute priority for ensuring the sustainability of the digital state and a key condition for scaling digitalization, rather than as an auxiliary function. In this regard, a comprehensive protection architecture is being formed, providing for increased responsibility for cybersecurity violations, the introduction of mechanisms for assessing and managing damage from cyber incidents, the development of the cyber insurance market, as well as the categorization of critically important digital objects.

     The contour will provide uniform requirements and end-to-end protection mechanisms: controlled access to data (including on the principles of "Zero Trust"), continuous monitoring and proactive detection of incidents, as well as unified approaches to managing access to sensitive data.

     Security will be integrated into digital platforms and processes throughout the entire solution lifecycle from design and development to industrial operation, which will ensure the transition from incident response to incident prevention through early detection of anomalies and vulnerabilities. To reduce systemic risks during data consolidation, advanced resource support for cybersecurity, competence development, and operational cyber resilience is provided.

     Technological sovereignty is fixed as one of the basic principles of the Strategy. Priority is given to the development and implementation of proprietary digital solutions, the development of national platforms and the localization of key technologies with the transfer of competencies. This will gradually reduce dependence on foreign platforms, licenses, and suppliers in critical areas, including identification, cybersecurity, data storage, and analytical systems. In terms of technological support, it provides for the diversification of solutions and suppliers, the development of national competencies and technology transfer mechanisms while maintaining compatibility with international standards.

     At the same time, technological sovereignty is considered not as isolation, but as the ability of the state to ensure the stability of digital infrastructure, manageability of digital processes, resistance to external constraints and control over strategic digital assets in the face of global competition.

     The digital transformation strategy involves a number of systemic risks, a significant part of which is taken into account and partially offset through institutional and technological mechanisms. However, two key groups of risks associated with implementation remain: internal and external.

     External risks include geopolitical risks and related challenges to technological sovereignty. Dependence on foreign technologies, platforms, and suppliers, as well as constraints arising from the global fragmentation of the digital space, can have an impact on the sustainability and continuity of digital transformation. A separate group of risks is represented by the volatility of world prices for raw materials, which form a significant share of budget revenues of the Republic of Kazakhstan, which affects the sustainability of financing the strategy in part provided by government sources.

     Internal risks include insufficient funding, strategic coordination, and bureaucratic processes that can delay the timing of key projects. International experience shows that one of the key threats is lack of coordination due to the lack of a single decision-making center and interdepartmental synchronization, which leads to fragmentation of initiatives, duplication of functions and reproduction of disparate digital solutions. There are also implementation risks associated with the need to ensure sustainable financing and synchronize investment cycles with the pace of technological change. Despite the envisaged mechanisms for attracting extra-budgetary funds, there remain potential limitations related to the willingness of the private sector to participate in large-scale digital projects. An additional factor is the inertia of budget procedures, which can lead to a shift in the timing of initiatives.

     To effectively implement the Strategy and mitigate internal risks, the Project Management Office (hereinafter referred to as the RMO) will become a single management and monitoring center. The Digital Headquarters under the Prime Minister of the Republic of Kazakhstan will operate at the coordination level, ensuring the prioritization of initiatives, interdepartmental synchronization and focus on achieving measurable effects. The RMO will use a digital portfolio management platform that aggregates data on all projects, key performance indicators, and results in near real time. AI technologies will be used to identify risks, interagency blockages, prioritize initiatives, and assess the contribution of projects to GDP growth, employment, and productivity. Quarterly implementation reviews will be conducted on the basis of AI control panels, in which the first managers will report on the achieved effects and make decisions on portfolio adjustments. Strategy implementation management will be based on the "data - analysis - solution -result" cycle.

     Personal responsibility for the implementation of digital and AI transformation will be assigned to the first heads of government agencies and quasi-governmental organizations with reference to the achievement of the Strategy's targets. She will be provided for: 1) a portfolio management model and regular monitoring of KPIs, including monitoring and evaluation of interim results; 2) the necessary resources (budgetary, extra-budgetary); 3) securing project teams and the necessary human (organizational) resources to implement changes.

     As a result, a state will be formed that operates on the basis of AI technologies and acts as a high-performance digital platform capable of managing socio-economic processes in close to real time, accompanying citizens and businesses along end-to-end life and economic trajectories, identifying risks before they materialize and ensuring the technological sovereignty of the Republic of Kazakhstan. This will ensure an increase in the productivity of the state apparatus by at least 25% by 2029.

     4. Conclusion

     The nationwide strategy of large-scale digitalization and total implementation of artificial intelligence technologies "Digital Qazaqstan" until 2029 captures the country's transition to a new stage of development, where digitalization and AI become not a set of IT projects, but the basic logic of the state apparatus, economy and social policy.

     The strategy is based on the progress made by the Republic of Kazakhstan in the field of digital services, fintech and computing infrastructure, but at the same time directly responds to the key systemic limitations of the current model - fragmentation of data and platforms, reactive regulation, the gap between digital solutions and real-life (economic) scenarios.

     The strategy sets a unified national course for building a full-fledged digital state over the next three years and the large-scale implementation of AI in all priority areas.

     For citizens, this means moving away from the bureaucratic "service on demand" model to an environment where the state becomes an invisible partner in life. People no longer adapt to departmental regulations, the system is built around their life situations, needs and potential. A society of equal digital access to education, healthcare, and employment is being formed.

     The Strategy sets a qualitatively new growth trajectory for the economy. Digitalization is no longer an auxiliary function and is becoming a systemic mechanism for increasing productivity. Industries are moving from disparate solutions to end-to-end digital circuits and a platform-based value chain management model.

For the state apparatus, Strategy means a deep institutional transformation. The state is moving to a compact management platform based on AI. The acceleration of the state itself is becoming key: flexible regulatory mechanisms, machine-readable law and adaptive budgeting are being introduced, synchronized with the real dynamics of technology and the economy.

     The implementation of the Strategy requires the discipline of a platform approach: the cessation of the creation of new disparate information systems without architectural necessity, the mandatory scalability of solutions, unified data management and the priority of results over the process.

     The strategy also establishes a new model of partnership between the state and the technology market: the state forms standards, architecture, demand and rules, while business and the domestic IT sector ensure the implementation, scaling and export of solutions with mandatory localization of competencies with the participation of international partners.

     The strategy involves reviewing the portfolio of digital initiatives and rejecting fragmented, showcase or departmental solutions that do not create a systemic economic or social effect. The priority of resource concentration is aimed at large-scale projects with a measurable contribution to economic productivity and sustainability, self-sufficiency and economic returns.

     The ultimate goal of Digital Qazaqstan is the formation of a proactive, technologically sovereign and secure digital state, where AI becomes a tool for increasing productivity and quality of life, a data-driven economy, and a fast and efficient government apparatus. The strategy ensures the transition of the Republic of Kazakhstan from digital maturity of services to digital maturity of management and competitiveness, creating the foundation for sustainable development of the country in the era of AI.

President    

Republic of Kazakhstan     

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