What Happens When the AI Boom Runs Out of Money

The AI race presents significant geopolitical and economic risks, as US dominance could incentivize adversarial responses like the destruction of critical semiconductor infrastructure. The current shift toward massive capital expenditure in AI compute and power mirrors historical industrial bubbles, where the primary challenge is bridging the gap between massive upfront investment and sustainable revenue generation. While hyperscalers like Amazon and Google leverage proprietary infrastructure to maintain competitive moats, others like Microsoft adopt a middleware strategy to capture enterprise value. Meta remains uniquely positioned to benefit from AI-driven ad optimization, provided it can navigate the transition from high-margin software to capital-intensive infrastructure. Ultimately, the long-term viability of this AI expansion depends on overcoming potential energy constraints and proving that intelligence can be monetized at scale, rather than just serving as a costly, unproven commodity.