'Zero Evidence' of AI Job Losses, Says Apollo Global Management Chief Economist
Key Takeaways
- ▸Slok claims 'zero evidence' of net AI-driven job losses, citing surging demand for AI specialists, data center staff, and infrastructure workers
- ▸The Jevons Paradox suggests efficiency gains from AI are driving increased consumption and employment of knowledge work, offsetting displacement
- ▸Tech layoffs attributed to AI may reflect overhiring and priority shifts rather than technology-driven redundancies
Summary
Apollo Global Management's chief economist Torsten Slok has challenged widespread concerns about AI-driven unemployment, asserting in a blog post that 'there is zero evidence of job losses because of AI.' Rather than causing net job losses, Slok argues the AI boom is actually boosting employment and wages across sectors most impacted by the technology, including semiconductors, data centers, energy, networking, and cloud infrastructure.
While acknowledging real workforce displacement, Slok reframes the AI revolution through the lens of the Jevons Paradox—the economic principle that efficiency gains paradoxically increase consumption. Despite AI making knowledge work cheaper, companies are consuming more of it, creating fresh demand for AI specialists, engineers, data center staff, and infrastructure workers. Tech giants cutting workers have simultaneously opened positions in other high-growth areas, supporting a narrative of labor market 'shift' rather than net 'loss.'
Slok concludes that the AI spending boom is simultaneously fueling employment growth and inflation pressures, suggesting the industry remains in an expansionary phase despite high-profile layoffs that critics argue are often cost-cutting measures labeled as AI-related reductions.
- AI spending boom is creating new high-wage opportunities in semiconductors, energy, networking, and cloud sectors
Editorial Opinion
Slok's 'zero evidence' claim is likely premature and may conflate job creation with job replacement. While it's true that AI has spawned new categories of high-skill work—data center technicians, prompt engineers—this ignores the real displacement happening in knowledge work roles being consolidated or eliminated by AI tools. The Jevons Paradox is an interesting framework, but history suggests technological disruption winners and losers rarely align geographically or demographically. Celebrating net job growth while real people face career obsolescence misses the critical equity question.
