Nobel Laureate Spence: AI Could Boost Productivity, But Won't Solve Growth Crisis

On May 18, Nobel laureate Michael Spence, a professor at Stanford Graduate School of Business and winner of the 2001 Nobel Prize in Economics, addressed the 2026 Tsinghua PBC Global Finance Forum in Chengdu, stating that artificial intelligence has the potential to drive significant labor productivity gains, though its effectiveness in resolving current economic pressures remains uncertain.

Global Economic Stability Under Pressure

Spence outlined a deteriorating global economic landscape, noting that the stabilizing factors that supported the global economy following World War II are gradually fading. He highlighted increasing geopolitical tensions and described the modern world as being “full of single points of failure,” where any localized disruption could trigger systemic fragility.

Rising Debt and Interest Rate Challenges

Across much of the world, Spence observed that real interest rates are climbing while debt levels are rising, damaging economic growth. He emphasized that the long-term impact of these pressures depends significantly on the duration of tensions in the Persian Gulf. Should these tensions persist, they could extend beyond energy price volatility to create actual energy shortages, fundamentally altering global economic development patterns.

AI as a Potential Counterbalance

Spence identified artificial intelligence as a potential offsetting factor from the supply-side perspective. While AI could theoretically drive a surge in labor productivity, he stressed that critical questions remain unanswered: how will this potential be realized, how strong will productivity gains be, and to what extent can productivity improvements address current pressures such as debt and sluggish growth? These, he noted, remain open questions.

China’s Strategic Focus on AI and Technology

Spence acknowledged China’s emphasis on artificial intelligence and technological development within its 15th Five-Year Plan. He noted that this potential depends not only on foundational model construction but also on the application of technology and its deep integration across social and economic sectors. China, he stated, has undertaken systematic planning and implementation to enhance the accessibility and inclusivity of financial services in manufacturing and service industries, ensuring broader societal benefits.

Cautionary Approach to AI Deployment

Spence stressed the importance of controlling AI use and avoiding excessive deployment, warning that uncontrolled expansion could introduce significant risks. He cautioned against assuming that machines will always perform optimally, emphasizing the need for a learning process to determine appropriate AI applications. Ultimately, Spence argued, society must discover the proper role for AI and develop effective frameworks for human-machine interaction and collaboration.