The artificial intelligence boom that has propelled stock markets to record heights may be running far ahead of the technology’s actual economic impact, according to a prominent hedge fund executive who warns that AI has not yet diffused across the economy to the degree necessary to justify current enthusiasm. Eric Peters, chief investment officer at One River Asset Management, is raising questions about whether the transformative potential of AI can match the extraordinary valuations now embedded in technology stocks and broader market indices.
Peters opened his recent commentary with an unlikely scene: President Trump seated in the Oval Office alongside Ukrainian President Volodymyr Zelensky, discussing whether the Ukrainian leader would dare travel to Moscow for potential peace negotiations. When Trump posed the question directly, Zelensky responded with dark humor that Ukrainian drones now populate Moscow’s skies, making such a visit dangerous. The exce, complete with laughter, exemplified humanity’s strange capacity to adapt to even the grimmest circumstances. Similar gallows humor has emerged around Iranian threats to target Trump with micro drones at Mar-a-Lago, prompting the former president to joke about his childhood sunbathing habits. What once seemed unthinkable, from wars involving major powers to casual discussion of assassinating heads of state, has become normalized in public discourse.
Yet beneath this adaptation to geopolitical chaos lies a financial market exhibiting its own form of complacency. Volatility has collapsed to levels typical of late cycle market behavior, with the VIX index settling around 15. Such low volatility mechanically forces investment strategies that control risk through volatility targeting to increase their market exposure, which in turn lifts equity prices and invites more volatility sellers into the market. Peters notes this dynamic has played out in every late market cycle, creating a self reinforcing feedback loop that eventually becomes almost comical in its predictability. Meanwhile, Russia’s wealthiest industrialist has begun hinting publicly that President Putin might resort to tactical nuclear weapons if cornered, a prospect that apparently no longer moves markets accustomed to existential threats.
While Western markets chase AI narratives with limited real world implementation, China has embarked on a comprehensive national strategy to embed artificial intelligence throughout its economy. In 2024, Beijing explicitly organized its industrial policy around six future industries focused on long term frontier technologies and six emerging pillar industries designed to drive near term economic output. By August 2025, Chinese authorities had formalized an Artificial Intelligence Plus initiative treating AI as foundational infrastructure comparable to electricity rather than a standalone sector. The strategy calls for deep integration of AI capabilities across all twelve priority areas, from embod artificial intelligence and brain computer interfaces to quantum technology, hydrogen and nuclear fusion energy, biomanufacturing, and next generation 6G mobile communications.
The six emerging pillar industries represent China’s effort to generate massive immediate economic output while reducing dependence on Western technology. Integrated circuits will support domestic semiconductor manufacturing designed to bypass American export controls. A low altitude economy encompasses drones, flying cars, and the infrastructure required to manage crowded airspace near ground level. Intelligent robots will automate factories and logistics networks. Aviation and aerospace initiatives include commercial spaceflight, satellite networks, and domestically produced commercial aircraft. Advanced energy storage will support grid scale battery deployment. Biomedicine covers cutting edge pharmaceuticals and medical equipment. Each pillar connects to AI capabilities that Chinese planners believe will create genuine productivity gains rather than speculative investment returns.
One chief investment officer who built his firm in Asia while investing in equities, technology names, and macro themes framed the competition starkly. China or the United States will dominate the AI era, he argued, dismissing European aspirations for sovereign artificial intelligence as unrealistic. European leaders may hope that Mistral or similar homegrown companies will provide large language models competitive with American and Chinese offerings, but the investment executive sees little chance of a third pole emerging in the global AI race. Scale, data, computational resources, and the willingness to rapidly deploy AI systems into production environments will determine which nation captures the economic benefits of the technology. On these dimensions, only two competitors appear positioned to compete at the highest level.
The fundamental question facing investors is whether current market valuations reflect realistic expectations about AI adoption timelines and economic impact. Peters suggests the technology remains in early stages of practical deployment, with most potential productivity gains still theoretical rather than realized. Markets have priced in a future where AI transforms every industry and creates trillions in economic value, yet the actual diffusion of these technologies into everyday business operations remains limited. As China systematically integrates AI across strategic industries while Western companies focus on developing ever larger foundation models, the gap between market expectations and economic reality may soon demand reconciliation. Whether that reckoning arrives gradually through disappointing earnings or suddenly through a volatility spike remains the critical uncertainty ing over an unusually complacent market.
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