AI Surveillance and Economic Governance in Central Asia: A Political Economy Analysis Using Secondary Data
In recent years, Central Asian states have increasingly integrated artificial intelligence (AI)-driven surveillance technologies into their governance frameworks. This paper examines how such technologies—ranging from biometric identification systems to predictive policing and smart city platforms—are reshaping economic governance across Kazakhstan, Uzbekistan, and Kyrgyzstan. Drawing on a comparative political economy approach and using publicly available secondary data from 2015 to 2025, the study investigates the evolving relationship between AI surveillance expansion, foreign direct investment (FDI), institutional reform, and the broader regulatory environment. The analysis synthesizes cross-national policy documents, governance metrics, economic indicators, and grey literature to map the political and economic correlates of AI adoption. Findings suggest that AI surveillance functions not only as a coercive tool for social control but also as a governance instrument aimed at projecting stability, attracting investment, and reinforcing regime legitimacy. While Kazakhstan and Uzbekistan deploy AI to centralize control and modernize bureaucratic infrastructure, Kyrgyzstan presents a more fragmented picture shaped by institutional volatility. The paper contributes to scholarship on digital authoritarianism by shifting focus from normative critiques toward understanding surveillance as a political-economic apparatus. It advances theoretical debates by situating AI surveillance within frameworks of authoritarian innovation and techno-governance, highlighting how digital infrastructures mediate state-market relations in non-Western contexts. Ultimately, the study underscores the need for nuanced inquiry into the economic rationalities underpinning surveillance regimes and calls for future research on their long-term implications for transparency, entrepreneurship, and sustainable development.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-06-17
- DOI
- https://doi.org/10.5281/zenodo.15695498
- Primary Topic
- Cybersecurity and Cyber Warfare Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00