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Jeremy Ney's avatar

Great article and looking forward to seeing more and more of these

Cyril Bladier's avatar

This is a very compelling framework, especially the distinction between “new work” and simply “more work.” The expertise scarcity cycle described here feels historically robust: new tasks emerge, scarce expertise commands a wage premium, then diffusion gradually erodes that premium. But generative AI may introduce a new variable into that cycle: temporal compression. Historically, the scarcity window could last decades, leaving enough time for workers to capture meaningful economic returns from newly valuable expertise. The open question is whether that mechanism still holds when AI systems can absorb, replicate and operationalize emerging cognitive skills within months. The issue may not be whether “new work” emerges. It probably will. The issue is whether the expertise premium survives long enough to stabilize labor share before commoditization catches up. That tension seems particularly important given Figure 1: recent new work has shifted heavily toward professional and managerial occupations, precisely the categories most exposed to current generative AI capabilities. So the mechanism historically offsetting automation may now be concentrating inside the zone most vulnerable to accelerated expertise diffusion. I suspect this is less a “future of work” question than a timing and governance question.

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