NextFin News - China is emerging as the definitive victor in the global artificial intelligence race, according to Jefferies strategist Mohit Kumar, who argues that a combination of depressed equity valuations and superior power infrastructure has created an insurmountable lead over Western rivals. Speaking on March 25, 2026, Kumar noted that while the United States remains locked in a high-cost arms race for proprietary frontier models, China has successfully pivoted toward a high-utility, open-source ecosystem that is already delivering tangible economic returns.
The shift in momentum is most visible in the explosive adoption of OpenClaw, an open-source AI agent framework that has become a cultural and industrial phenomenon across the mainland. According to Fortune, tech giants like Tencent and Baidu have moved beyond mere development, hosting mass "install-fests" where engineers help thousands of citizens deploy autonomous agents on personal hardware. This grassroots "lobster craze"—a play on the software’s crustacean branding—contrasts sharply with the American landscape, where AI remains largely centralized within the walled gardens of a few trillion-dollar firms.
Kumar’s thesis rests on two pragmatic pillars: the cost of entry and the capacity to scale. Chinese AI firms are currently trading at a significant discount compared to their Silicon Valley counterparts, despite achieving parity in many open-source benchmarks. This valuation gap, according to Jefferies, offers a "margin of safety" for investors that no longer exists in the U.S. tech sector, where Nvidia-driven multiples have left little room for error. Furthermore, China’s aggressive investment in power infrastructure—specifically the networking and cooling systems required for massive inference—is now paying dividends as the U.S. faces mounting energy constraints and regulatory hurdles for new data centers.
The competitive landscape has been further tilted by the "distillation" of Western intelligence. Anthropic recently accused Chinese firms including DeepSeek and Moonshot AI of extracting knowledge from its Claude models to bolster their own frameworks. While such allegations highlight the friction in intellectual property, the result is a rapid narrowing of the capability gap. Alibaba’s Qwen model has already found its way into the backends of Western companies like Airbnb, proving that the "Made in China" label in AI is no longer a barrier to global enterprise adoption.
For U.S. President Trump, the challenge is now one of industrial policy rather than just chip bans. While the administration has focused on blocking high-end hardware, the Chinese ecosystem has adapted by optimizing for efficiency and open-source collaboration. Kumar suggests that the "AI disruption trade" is no longer about who builds the biggest model, but who integrates it most effectively into the real economy. In this regard, China’s ability to mobilize its population around tools like OpenClaw suggests a level of societal integration that the West has yet to match.
The financial implications are already rippling through global markets. As U.S. internet stocks face warnings from Jefferies about squeezed profit margins and "AI disintermediation" risks, Chinese tech shares are being viewed as a value play with high-growth potential. The era of American AI exceptionalism is being tested by a Chinese model that prioritizes accessibility and infrastructure over proprietary dominance, a strategy that Kumar believes will define the next decade of market leadership.
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