Michael

The implications for AI

So what does that tell us about AI? Our mental model often defaults to an industrial image—John Henry versus the steam drill—where jobs are one dominant task, and automation maps one‑to‑one: Automate the task, eliminate the job. The internet revealed a different reality: Modern roles are bundles. Technologies typically hit routine tasks first, then workflows, and only later reshape jobs, with second‑order hiring around the backbone.

That complexity is what made disruption slower and more subtle than anyone predicted. AI fits that pattern more than it breaks it. The text-generating AI known as large language models can draft briefs, summarize medical notes and answer queries. Those are tasks—important ones—but still parts of larger roles. They don’t manage risk, hold accountability, reassure anxious clients or integrate messy context across teams.

Expect a rebalanced division of labor: The technical layer gets faster and cheaper; the human layer shifts toward supervision, coordination, complex judgment, relationship work and exception handling.

What to expect from AI, then, is messy, uneven reshuffling in stages. Some roles will contract sharply—and those contractions will affect real people. But many occupations will be rewired in quieter ways. Productivity gains will unlock new demand and create work that didn’t exist, alongside a build‑out around data, safety, compliance and infrastructure.

AI is unprecedented; so was the internet. The real risk is timing: overestimating job losses, underestimating the long, quiet rewiring already under way, and overlooking the jobs created in the backbone. That was the internet’s lesson. It’s likely to be AI’s as well.