Apollo Economist Says AI Will Mirror China's WTO Boom, Not Bust

Torsten Sløk, Apollo Global Management's chief economist, sees artificial intelligence following the same job-creating pattern as China's 2001 WTO entry. According to Bloomberg, Sløk argues that while AI will disrupt white-collar work initially, the productivity gains will ultimately generate more employment than they eliminate. This mirrors what happened when China's manufacturing surge first threatened US factory jobs but eventually contributed to broader economic expansion and new job categories.

The economic framework Sløk presents has direct implications for open-source AI development. If AI follows the China shock pattern, the focus shifts from job replacement to job creation through new applications and services. Open-source projects that democratize AI capabilities could accelerate this job creation effect by enabling smaller companies and individual developers to build AI-powered businesses. This suggests that open-source AI tools might be more economically beneficial than proprietary systems in the long run, as they lower barriers to entry for new AI-driven ventures.

Developers can stop worrying about coding themselves out of jobs. Sløk's analysis, drawing on Jevons paradox from economics, suggests that making AI more efficient actually increases demand for human oversight, customization, and new applications. The parallel to China's WTO entry shows that initial displacement in specific sectors gets offset by growth in adjacent areas. For developers, this means focusing on AI integration, specialized applications, and human-AI collaboration tools rather than competing directly with AI. The economic expansion creates more niches for technical talent than it eliminates.

Enterprise leaders can accelerate AI adoption without fear of workforce collapse. Sløk's framework indicates that companies implementing AI will see productivity gains that enable expansion into new markets and services, requiring more human workers overall. This reframes AI investment from a cost-cutting measure to a growth strategy. The China shock analogy suggests that early adopters who embrace AI productivity gains will capture disproportionate market share, similar to how companies adapted to China's manufacturing integration gained competitive advantages.

The economic data will tell the story before the job market does. CNBC reports that Sløk notes AI's impact isn't yet visible in macroeconomic data, suggesting we're still in the early disruption phase. As productivity gains start appearing in quarterly reports, expect increased corporate AI investment followed by gradual job market expansion. The timeline likely mirrors China's WTO integration: initial 2-3 years of disruption headlines, followed by 5-7 years of net job creation as new AI-driven industries emerge. Watch for early signals in sectors like AI consulting, AI-human collaboration tools, and entirely new service categories that don't exist yet.