The World Bank has raised concerns that Central Asian countries are on a path to becoming passive consumers of artificial intelligence rather than active contributors to its development. The warning, reported by Kursiv Media, reflects a broader pattern of technological dependency that could limit the region’s economic potential and long-term competitiveness in a rapidly shifting global landscape.
The report highlights that while AI adoption is growing across Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan, the region lacks the foundational infrastructure, skilled workforce, and policy frameworks needed to produce original AI solutions. Without deliberate intervention, Central Asia may find itself importing AI tools built elsewhere, shaped by foreign priorities, and offering little room for local adaptation or ownership.
The Gap Between Adoption and Creation
There is a meaningful difference between using AI and building it. Many Central Asian businesses and government institutions are beginning to integrate AI-powered tools into their operations, from automated customer service to data analytics platforms. However, the underlying models, algorithms, and systems powering these tools are almost entirely developed outside the region, primarily in the United States, China, and Europe.
This dependency creates several risks. Local languages, cultural contexts, and specific economic conditions are often underrepresented in globally trained models. When AI systems are not built with local data and local needs in mind, their outputs can be less accurate, less relevant, and sometimes outright misleading for users in the region.
Infrastructure and Talent as Core Challenges
The World Bank points to two primary obstacles standing between Central Asia and meaningful AI development: digital infrastructure and human capital.
Reliable high-speed internet, data centers, and computing power remain unevenly distributed across the region. Rural areas in particular lag significantly behind urban centers, creating a two-tier digital environment that limits both access to AI tools and the ability to collect the large datasets that AI systems require to function effectively.
On the talent side, the region produces relatively few graduates with advanced skills in machine learning, data science, and software engineering. Many of those who do acquire these skills emigrate to higher-paying markets in Russia, Europe, or North America – a brain drain that consistently depletes the local pool of technical expertise.
- Kazakhstan has made the most visible investments in digital infrastructure and AI strategy among the five countries
- Uzbekistan has launched several government-backed digitalization programs in recent years
- Kyrgyzstan, Tajikistan, and Turkmenistan face more significant structural barriers related to connectivity and education systems
Policy Frameworks Still Catching Up
Beyond infrastructure and talent, the regulatory environment across Central Asia remains underprepared for the demands of an AI-driven economy. Data governance laws, intellectual property protections for software, and clear frameworks for AI accountability are either absent or in early stages of development in most countries in the region.
Without these legal foundations, it becomes difficult to attract foreign investment in AI research, protect locally developed innovations, or build public trust in AI systems used in sensitive areas like healthcare, finance, or public administration.
The World Bank recommends that governments in the region prioritize the development of national AI strategies that go beyond surface-level digitalization goals. These strategies should address data sovereignty, support for local startups, investment in university-level AI research, and cross-border cooperation within the region itself.
Regional Cooperation as a Potential Lever
One area where Central Asia could gain an advantage is through coordinated regional action. The five countries share linguistic ties, overlapping economic structures, and common challenges that make collaborative AI development a logical step. A shared approach to data standards, joint research initiatives, and pooled computing resources could help smaller economies punch above their weight in the global AI race.
There are already some early examples of cross-border digital cooperation, though these remain limited in scope. Expanding such efforts into the AI domain would require political will and sustained funding – neither of which has been consistently available in the region.
What Is at Stake
The consequences of remaining a passive AI consumer extend beyond the technology sector. AI is increasingly embedded in agriculture, logistics, energy management, and public services – all sectors that are central to Central Asian economies. If the tools governing these sectors are designed and controlled externally, the region’s ability to make independent decisions about its own development becomes constrained.
The World Bank’s message is not that Central Asia is failing, but that the window for building genuine AI capacity is open now and will not remain so indefinitely. Countries that invest early in the right foundations – education, infrastructure, regulation, and research – will be far better positioned to shape how AI works for their populations rather than simply accepting what others have built.
The region has navigated significant economic and political transitions over the past three decades. Whether it can translate that resilience into technological self-sufficiency in the AI era remains an open question, but the groundwork laid in the next few years will likely determine the answer.