1. The global AI race, initially celebrated as a technological and financial triumph, is now raising concerns among economists about a macroeconomic "hangover." While AI promises to boost supply, it simultaneously threatens to suppress labor income, weaken consumer demand, and trigger long-term deflationary pressures. These issues were central to a forum on AI's new economic growth paradigm at the 2026 Inclusion Conference on the Bund in Shanghai. [para. 1][para. 2]
2. For China, this technological shift arrives during a sensitive macroeconomic period. The world's second-largest economy faces a structural imbalance of strong supply and weak demand, worsened by a real estate downturn and cautious consumer spending. Historically, policymakers relied on supply-side expansion and infrastructure investment, but economists warn that if AI disproportionately benefits capital owners over laborers, it could transform this cyclical headwind into a long-term structural crisis. [para. 3][para. 4]
3. Huang Yiping, dean of the National School of Development at Peking University, referenced the Solow paradox—computers appearing everywhere except in productivity statistics—to caution that AI will not deliver an immediate, massive surge in economic growth. While optimistic about AI's long-term productivity potential, he noted that staggering investment levels may either translate into sustained gains or inflate a technological bubble. More critically, AI's expansion of supply could impact employment and widen the wealth gap, suppressing consumer demand and potentially calcifying China's supply-demand dilemma into a chronic condition. [para. 5][para. 6][para. 7][para. 8][para. 9]
4. Luo Zhiheng, chief economist at Yuekai Securities, echoed these concerns, noting that AI investment is boosting China's supply chain exports and tech stock valuations short-term, but this is offset by the real estate market's decline. He characterized AI as a double-edged sword: it expands supply through efficiency gains, but as a capital-intensive industry, it reduces labor compensation's share in national income, constraining household earnings and exacerbating the supply-demand imbalance. [para. 10][para. 11]
5. Han Xinyi, CEO of Ant Group, argued that the AI economy cannot rely solely on capital injections or mere efficiency gains. If AI only substitutes labor without creating incremental new demand, it could trigger fresh crises of supply-demand imbalance and mismatched investment returns. [para. 12]
6. On prices, Miao Yanliang, chief economist at China International Capital Corp., noted that major technological revolutions historically coincided with deflationary periods, as supply expansion typically outpaces demand. AI's diffusion is unprecedented in speed—large language models reached nearly 50% penetration in three to four years, versus 30 years for PCs and the internet. This hyperspeed has concentrated demand for upstream resources, with memory chip prices spiking over 600% during the AI boom, though Miao predicts this bottleneck effect will subside within three to five years. [para. 13][para. 14][para. 15][para. 16]
7. Long-term, Miao anticipates AI acting as a powerful deflationary force. The substitution effect will likely reduce labor's income share, and because capital owners have lower marginal propensity to consume than laborers, this shift suppresses aggregate demand. Additionally, corporate expectations are optimistic while consumer sentiment deteriorates, creating uncertainty. Miao advocated for structural fiscal adjustments, tax reforms, retraining programs, and state-backed job creation to combat these pressures. [para. 17][para. 18][para. 19]
8. In the labor market, Miao noted a positive correlation between income levels and AI exposure, but high exposure doesn't equal immediate unemployment—individual tasks are automatable while entire professions remain harder to replace. Xing Ziqiang of Morgan Stanley emphasized that AI's adoption timeline is compressed to a single decade, versus decades for past breakthroughs, affording less time for workforce adaptation. While AI elevates experienced workers' productivity, it threatens entry-level positions. [para. 20][para. 21][para. 22]
9. Addressing employment challenges requires empowering individuals rather than protecting obsolete roles. Han suggested giving workers and small businesses access to low-cost AI products, modernizing education and vocational training to emphasize judgment, creativity, and adaptability, and refining secondary wealth distribution mechanisms with comprehensive social security frameworks to support displaced workers during the transition. [para. 23]
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