ASTANA — Financial institutions across Central Asia are accelerating the adoption of artificial intelligence, with 36% already using AI technology and 56% planning to implement it within a year, according to a report released by the National Bank of Kazakhstan on February 13.
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The study provides the region’s first comprehensive assessment of AI, based on a survey of 232 financial institutions in Kazakhstan, the Kyrgyz Republic, and Tajikistan. integration in financial markets.
Despite strong interest, implementation is still in its early stages. 38% of respondents are conducting research, 28% are running pilots or partial projects, and only 2% have reached full-scale deployment.
“In 2026, the National Bank will focus on the transition to the practical implementation of the digital asset market and its integration into Kazakhstan’s existing financial system. The plan also includes the development of an integrated AI ecosystem, the creation of a platform of specialized AI agents within the bank, and regional cooperation in AI to develop practically applicable AI solutions,” said National Bank Governor Timur Suleymenov in the paper’s foreword.
He says this approach allows for systematic risk management. preparation As AI agents, autonomous systems that can perform tasks with limited human oversight, become more complex, they must also comply with regulatory requirements.
This digital asset initiative is part of a broader shift towards AI-assisted supervisory and agent-based systems that automate analytical and monitoring functions in the financial sector.
From operational automation to strategic utilization
The report shows that AI adoption in Central Asia is gradually moving beyond basic process automation to predictive analytics and risk-focused applications. Early introduction focused on improving operational efficiency. Financial institutions are now increasingly applying AI to fraud detection, credit scoring, and customer data analysis to support decision-making.
In Kazakhstan, 75% of banks are using AI and 88% plan to expand its application. However, implementation remains focused on transactional and customer-facing areas, particularly credit scoring and fraud prevention systems. Its use in strategic planning, compliance monitoring, and comprehensive risk management remains limited and primarily in the early stages of implementation.
The report also highlights the growing importance of generative AI, systems that can generate text, images, and other content, and AI agents that can perform semi-autonomous tasks.
worldwideagent-based AI systems are predicted to grow at an average annual rate of 45% over the next five years. US-based research firm Gartner predicts that by 2027, AI agents could participate in or support 50% of business decisions. McKinsey data cited in the report suggests that re-architecting workflows around AI agents can reduce task execution times by 60% to 90%, depending on the application.
Global expansion, regional readiness gaps
This study places Central Asia within the rapidly expanding global AI landscape. Enterprise investment in AI will reach $252.3 billion in 2024, an increase of 26% from 2023. Investments have increased almost 13 times over the past 10 years.
According to an international study referenced in the report, 78% of organizations worldwide are currently using AI in at least one business function, up from 55% in 2023. At the same time, the cost of AI model inference, the process of generating results from a trained model, has fallen 280 times since 2022, reducing barriers to entry for small and medium-sized enterprises through cloud-based low-code platforms.
Despite these global advances, Central Asian countries remain outside the top 50 in AI readiness rankings. In 2024, Kazakhstan was ranked 76th in the world, Uzbekistan 70th, Tajikistan 131st, and Kyrgyzstan 134th. The report identifies technological maturity and human capital development as key constraints slowing regional convergence.
Capacity, governance, and risk considerations
Across the three countries, a lack of experts with combined expertise in finance, data analytics, and risk management is a major constraint to widespread AI adoption. Apart from computing infrastructure, sustainable AI integration also requires organizational preparations such as trusted data systems and a coordinated governance framework.
Data fragmentation, inconsistent quality standards, and limited access to advanced computing resources constrain expansion beyond pilot programs. For example, in Tajikistan, 65% of financial executives believe AI is very important to their future competitiveness, but 33% of institutions are currently using AI. Most innovation projects are still pilot-based and not yet integrated into core business processes, so their overall impact is limited.
In the Kyrgyz Republic, regulators are prioritizing the use of AI in payment monitoring, compliance automation, and supervisory analytics. The report shows that institutional responses, such as unified risk management approaches and secure cross-border data exchange, remain common challenges across the region.
The regulatory landscape is evolving as technology expands. More than 10 countries have established AI safety institutes to develop standards for safe deployment. Although frameworks such as the European Union’s AI law require the labeling of AI-generated content, only 38% of systems worldwide have implemented watermarking mechanisms.
Cybersecurity risks are also increasing. According to research cited in the report, 68% of organizations in the US and UK have experienced a data breach related to the use of AI tools by their employees. In comparison, only 23% have a comprehensive AI security policy in place.
Environmental impacts add another dimension to policy considerations. Global data center energy consumption has increased by 72% and annual water use has reached 560 billion liters. At the same time, AI-enabled technologies are being applied to improve efficiency in agriculture, logistics, and energy management.
Strategic impact on Central Asia
The report showed that AI in Central Asian financial markets is no longer limited to experiments. Adoption rates and planned expansion suggest structural change, but structural constraints in infrastructure, human capital, and regulatory capacity continue to limit large-scale consolidation.
For foreigners investor This data highlights regions in transition that are actively keeping pace with global AI trends and investing in supervisory capabilities and digital infrastructure, but facing tangible constraints in talent, scale, and technology depth.
