At the "AI Economic Growth Paradigms and Social Value Reconstruction" forum, held during the 2026 Inclusion·Outer Temple Conference on September 9th, Nobel Economics Laureate and New York University Professor Thomas Sargent delivered remarks asserting that China and the broader Asian region are set to be decisive forces in shaping the worldwide AI competitive environment.
Addressing the intensifying global race for AI supremacy, Sargent argued that evaluating returns on AI investment must transcend mere technological progress and incorporate the dynamics of global competition. He observed that both Asia and the United States are rapidly escalating their AI expenditures, with the latter being particularly pronounced. There, a small cohort of corporations is locked in a race of escalating commitments. However, the professor cautioned that such massive capital outlays do not automatically guarantee profitable outcomes.
"These investments are predicated on uncertain models. No one truly knows what these models will ultimately produce," Sargent stated. While AI technology holds the promise of productivity gains and novel business value, he emphasized that the realization of expected returns for investors remains highly speculative. In his view, a frequently underestimated variable in this calculation is the competitive pressure emanating from Asia.
Sargent highlighted two critical prerequisites for today's rapid AI progress: vast datasets and immense computational power. He pointed to China as a frontrunner in leveraging big data applications, particularly in foundational fields like physics. "China possesses extensive data resources and formidable computing capabilities," he noted. This combination means Asia cannot be relegated to the role of a follower in the AI race. Given AI's growing dependence on continuous iteration across data, computation, and model capabilities, the Chinese and Asian markets, endowed with these essential elements, will directly shape the global industry's trajectory.
Furthermore, Sargent underscored that frontier methodologies in AI are disseminating rapidly. He cited Chinese large language models such as Tongyi Qianwen and DeepSeek as active adopters of these advanced techniques. Consequently, technological prowess is unlikely to remain concentrated indefinitely within a single nation or among a few select corporations. He suggested that projecting an AI company's long-term value based on the assumption of sustained technical superiority and high profit margins is a premise worthy of reconsideration.
"Investors are drawn in by the pursuit of profit, but they may not necessarily secure those returns," Sargent warned, encapsulating the uncertainty that pervades the current investment climate.