Prediction 5 Revisited: I Said AI Augments Workers, Mass Unemployment Is Overstated. I Stand By It. The Crack Is Entry-Level.

In January 2025 I predicted augmentation over replacement — accountants becoming analysts, prompt engineering as a hot skill, ‘Grandma AI’ passing expert wisdom to systems. Broadly correct. But a faul

This is the prediction I most want to be right about, which is exactly why I need to be hardest on it.

Prediction five: fears of mass unemployment prove overstated. Roles transform rather than vanish. Specialized fields keep humans for oversight and interpretation. New skills — prompt engineering, data literacy — become sought-after. My favorite framing was ‘Grandma AI with Superpowers’: the human expert as the grandmother passing generational wisdom to a fledgling AI system.

The augmentation thesis held at the aggregate

No AI jobpocalypse arrived. The mass-unemployment headlines of early 2023 did not materialize into 2025-2026 reality. What happened instead is exactly the role transformation I described: the wealth-management analyst who now supervises AI rather than building models by hand, the lawyer reviewing AI-drafted discovery, the radiologist using AI as a second reader. EY’s 2025 survey found 95% of wealth-management firms using generative AI somewhere. The work changed shape. The headcount didn’t collapse wholesale.

And ‘Grandma AI’ turned out to be a genuinely good frame. The most valuable humans in 2026 aren’t the ones who can do the task — they’re the ones with the contextual, hard-won judgment to know when the AI’s output is subtly wrong. The expert as mentor to the machine. That’s holding up better than most of my 2025 metaphors.

The crack I underweighted: the ladder lost its bottom rung

Here’s where I have to be honest. I framed augmentation as broadly good news for workers. The data forming through 2025-2026 says: good news for senior workers, brutal news for juniors.

The tasks AI handles best are exactly the entry-level tasks — the document review, the first-draft research, the basic coding, the junior analyst grunt work that used to be how you broke into a field. When AI does up to 90% of those tasks (my own prediction 12 said as much), the entry-level job doesn’t transform. It thins out. And if you eliminate the bottom rung, you eventually have no seniors, because seniors are just juniors who survived a decade. I called the augmentation. I underweighted the generational discontinuity it creates.

This is the bifurcation I now write about constantly: the elite few with AI leverage become dramatically more productive, while the people who would have learned the trade on the bottom rung find the rung gone. The aggregate unemployment number stays calm. The distribution underneath it gets violent. Both things are true. My January 2025 self emphasized the calm aggregate and didn’t look hard enough at the violent distribution.

Prompt engineering: right skill, wrong shelf life

I called prompt engineering a hot skill. It was — for about a year. Then the models got good enough that elaborate prompt-craft mattered less and ‘context engineering’ and agent orchestration mattered more. I had the right idea (new AI-collaboration skills become valuable) attached to a job title with a two-year half-life. The meta-lesson: when you predict a hot skill in AI, predict the category, not the title. The titles rotate every eighteen months.

The next 12 months: the missing-rung problem goes from anecdote to policy

My forecast for May 2027: the entry-level squeeze becomes a named political and corporate problem. Expect the first serious ‘where do juniors come from now’ panic in knowledge-work fields — law, consulting, accounting, software. Companies that quietly stopped hiring juniors in 2025-2026 discover in 2027 that their senior pipeline is drying up, and the smart ones start building deliberate human-apprenticeship-alongside-AI programs as a competitive advantage.

The augmentation thesis survives, but it gets a mandatory asterisk: augmentation is great if you’re already on the ladder. The defining workforce question of the next year isn’t ‘will AI take jobs’ — that framing is dead. It’s ‘who builds the ladder back, and who gets left standing under where it used to be.’

I’d give my January 2025 self a B+. Right that the apocalypse wouldn’t come. Too optimistic about who’d be fine when it didn’t.

Sources: original forecast (Jan 6 2025); EY 2025 wealth-management AI survey; MIT findings on white-collar task automation; entry-level/junior labor-market analysis 2025-26; the author's own prediction 12 (90% of certain job tasks automatable).