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The post-pandemic period marked a turning point in global debates over politics, economics, and governance. In late 2022, the release of ChatGPT accelerated the shift from abstract discussions of artificial intelligence to its everyday relevance.
Although AI had long existed in academic, military, and corporate spheres, its mass accessibility transformed it into a prominent global phenomenon.
By 2024–2025, AI became integrated into public administration, national development strategies, and geopolitical competition, raising questions about sovereignty, power, inequality, and the future of governance.
Central Asia is already part of this story. Across the region, artificial intelligence is becoming more than a new technology; it is a governance challenge with implications for economic resilience and the future of regional cooperation.
Recently, President of Kazakhstan Kassym-Jomart Tokayev declared 2026 the “Year of Artificial Intelligence,” signalling Astana’s ambition to become a regional leader in digital governance and innovation. In 2025, Kazakhstan became the first country in the region to establish a dedicated Ministry of Artificial Intelligence.
In Uzbekistan, government programmes aim to enhance national AI capacity through substantial investments in human capital and digital infrastructure.
The country will allocate $100 million to develop a national AI ecosystem in collaboration with global heavyweights such as Nvidia. This ecosystem will focus on supercomputing clusters and specialist training to strengthen export-oriented IT sectors.
Tajikistan is advocating for a Regional AI Centre in Dushanbe. The proposal focuses on coordinating research, training, and regulatory frameworks across Central Asia. Kyrgyzstan has also put forward the idea of a Regional AI Hub as part of broader digital cooperation initiatives.
Private innovation is also emerging. One example is a Kazakh startup that has developed a large-scale speech recognition model for Turkic languages. It addresses regional linguistic needs often overlooked by global AI systems.
However, this rapid political embrace raises a critical question for regional integration. Will AI promote cooperation through shared standards, interoperability, and collective governance frameworks, or will it widen disparities between emerging digital leaders and laggards?
Artificial intelligence should be viewed not just as a tool for automation but as a governance technology. This system will reshape how states collect data, make decisions, allocate resources, and interact with citizens.
Unlike previous waves of digitalisation, AI introduces algorithmic decision-making into public administration, affecting social welfare distribution, taxation, urban planning, border control, and public service delivery. By 2025, approximately two-thirds of OECD governments were expected to use AI to enhance public service design and delivery, highlighting its rapid integration into core state functions.
In Central Asia, where state capacity has traditionally depended on centralised models, AI offers efficiency gains while reinforcing the state as the main regulator of digital transformation.
Governments increasingly see AI as a tool to improve bureaucratic performance, reduce corruption, and build public trust. However, algorithmic governance raises concerns about transparency, accountability, and the potential reproduction of social inequalities through data-driven systems.
One of the main drivers behind the AI race in Central Asia is economic expectation. According to assessments by the World Trade Organisation and the McKinsey Global Institute, artificial intelligence could add up to $15.7 trillion to the global economy by 2030.
This growth would come from productivity gains, new business models, and technological spillovers. This consensus underscores AI's emergence as a key pillar of global economic competition.
Central Asian states, like many emerging economies, are acutely aware of these dynamics. Kazakhstan has actively promoted its digital ecosystem, emphasising innovation hubs, fintech development, and AI-based startups. Policymakers often point to high-profile success stories as evidence of the region’s potential.
These include regional AI firms securing international contracts and generating revenue in advanced markets such as the United States and Europe.
However, the political economy of AI in Central Asia remains fragile. Despite notable initiatives, the region faces structural constraints: limited domestic markets, dependence on external capital, skills shortages, and uneven digital infrastructure.
Moreover, the World Bank has projected that growth in Central Asia could moderate toward the mid-2020s due to external shocks, commodity price volatility, and structural vulnerabilities. These developments could, in turn, limit investment in advanced technologies.
In this context, AI is often presented as a solution. Yet whether it can offset broader economic slowdowns remains uncertain.
This tension reveals a central paradox: AI is promoted as both a tool for economic diversification and a symbol of modernity, even as fundamental economic conditions across the region remain uneven.
From the perspective of regional integration, artificial intelligence represents both a strategic opportunity and an emerging risk for Central Asia. On the one hand, AI creates concrete opportunities to harmonise digital standards, develop interoperable platforms, and align regulatory frameworks across borders.
Global case studies show that AI-enabled systems in customs, logistics, and public administration can reduce transaction costs by 10–30%. These technologies also significantly improve coordination, especially in regions with fragmented governance.
In sectors such as trade facilitation, transport corridors, e-government, and education, shared AI-driven solutions could strengthen institutional interoperability and reinforce existing regional cooperation mechanisms.
On the other hand, the uneven pace and scale of AI adoption among Central Asian states risks creating digital fragmentation rather than convergence. Kazakhstan's relatively advanced digital infrastructure, regulatory experimentation, and investment capacity sharply contrast with the more cautious or resource-constrained approaches of some neighboring countries.
If AI development primarily follows nationally driven strategies without meaningful regional coordination, technological disparities may widen rather than narrow. Such divergence would undermine prospects for a shared digital space and weaken AI's integrative potential.
Importantly, digital fragmentation is not just a technical issue; it has significant political implications. States with greater AI capacity may gain disproportionate agenda-setting power within regional institutions, shaping norms, standards, and priorities to reflect their own technological advantages.
Conversely, countries with limited AI capabilities risk becoming passive technology consumers, dependent on external providers or more advanced regional partners. These disparities could complicate existing mechanisms of regional cooperation, reinforce hierarchical relationships, and shift integration dynamics from cooperative to competitive.
The regional AI landscape in Central Asia is further influenced by broader geopolitical forces. The global competition over AI governance, primarily involving the United States, China, and the European Union, extends into the region through infrastructure projects, cloud services, data governance models, and regulatory frameworks. Central Asian states navigate these external pressures through pragmatic, multi-vector strategies.
Their goal is to maximise technological benefits while preserving regulatory autonomy and political sovereignty. However, AI introduces new forms of dependency that are less visible than traditional economic or security ties.
Artificial intelligence thus becomes a venue for geopolitical bargaining. Decisions regarding data localisation, cloud infrastructure providers, algorithmic standards, and cybersecurity partnerships carry long-term strategic implications.
Individual Central Asian countries lack the scale and resources to develop fully autonomous AI ecosystems. Uncoordinated engagement with competing external actors risks locking them into incompatible technological systems. This issue undermines regional interoperability and further entrenches fragmentation.
Beyond geopolitics and economics, AI raises significant societal and ethical questions across Central Asia. Public debate on AI governance remains limited but is gradually expanding, particularly within academic communities and civil society.
Concerns around labor displacement, surveillance, data privacy, and algorithmic bias are becoming more prominent, particularly as AI becomes embedded in public administration and social governance. In settings marked by uneven institutional trust, the use of opaque algorithmic systems may amplify public skepticism instead of reinforcing institutional legitimacy.
The introduction of AI into governance structures heightens these concerns. While algorithmic decision-making can improve efficiency and limit administrative discretion, it also risks weakening political accountability if the decision-making logic remains inaccessible to citizens. The absence of clear, regionally adapted ethical frameworks exacerbates this challenge.
Ultimately, whether AI will divide or integrate Central Asia remains unclear. The answer depends less on technology than on political choices and governance strategies. AI can act as a catalyst for regional cooperation if states prioritise shared standards, institutional dialogue, and collective capacity-building.
Otherwise, fragmented national approaches risk reproducing existing inequalities and deepening regional divides. Central Asia is at a crossroads: how it governs AI will define both its digital future and regional unity.
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