STRATEGIC OPTIMIZATION OF NATIONAL AI INFRASTRUCTURE: A GAME-THEORETIC AND COMPARATIVE ANALYSIS OF ARMENIA’S EMERGING AI DATA CENTER ECOSYSTEM
Aren MKHITARYAN
Zhejiang University, China
arenmkhitar@gmail.com
Abstract
Armenia’s decision to host one of the world’s largest AI GPU clusters — a $500 million Phase 1 scaled to
a $4 billion, 50,000-GPU megaproject in partnership with Firebird AI, NVIDIA, and the United States
Government — constitutes the most consequential economic policy gamble in the country’s postindependence history. This paper conducts a comprehensive, multi-disciplinary analysis of that gamble
across seven dimensions: macroeconomic and technological impact, formal game-theoretic modelling,
national strategy optimization, risk and constraint analysis, comparative benchmarking, scenario
forecasting, and synthesis into a dominant national strategy. Using a Stackelberg-signalling framework
nested within a repeated cooperation game, we identify four strategic equilibria governing Armenia’s
position. Drawing on data from Armenpress, EVN Report, PR Newswire, Bloomberg, and peer-reviewed
literature on small-state technology strategy, we model transmission channels from the $4 billion capital
injection to Armenia’s $25.79 billion economy and find a potential 1.5–2.5 percentage point growth
contribution during construction, declining to a 0.4–0.6 point permanent productivity uplift contingent on
domestic absorptive capacity. Comparative analysis of the UAE, Singapore, Ireland, and Estonia yields an
integrated policy scorecard. Three probability-weighted scenarios are developed. We conclude that
Armenia’s dominant strategy is conditional deep integration — locking in US alignment as a costly
separating signal while building an Estonia-style digital governance layer, implementing Singapore-style
selective data centre licensing, and compounding geopolitical hedges through India, France, and EU
accession. The 24–36 month execution window for this strategy is narrow and closing.

