What jobs are safe from AI?
Status as of 2026-09-05
- Microsoft Research, “Working with AI” (Jul 2025, CC-BY-4.0, 785 occupations): the highest AI-applicability score is Interpreters and Translators at 0.49 — the share of an occupation’s work activities Copilot users were observed doing with AI. It measures observed applicability, not job loss. Look up your own occupation on the AI job exposure check.
- Indeed Hiring Lab (2026-07-08): the most AI-exposed occupations’ job postings fell the most — and then rebounded the most; 71% of software-development posting growth May 2025→May 2026 was senior-level.
- Stanford “Canaries in the Coal Mine” (Aug 2026 update): a ~19% relative employment gap for ages 22–25 in the most AI-exposed occupations; older workers and less-exposed occupations show no comparable decline — “safe” is currently as much about seniority as about job title.
Start here if the question is about your own job: Should you be worried about AI taking your job? →
The principle, not a list of job titles
Predictions about specific titles age badly. The durable signal is what kind of work the current autonomy gap protects. AI is strong at scoped, digital, well-specified tasks (~80% SWE-Bench Pro, ~83% GDPval) but weak at reliable, accountable, long-horizon ownership without a human in the loop. That gap — the same one keeping AGI-2027 graded Open — maps directly onto which work is exposed.
| More exposed (near-term) | More durable (near-term) |
|---|---|
| Task-bounded, fully digital | Reliable unsupervised judgment & accountability |
| Well-specified, repeatable outputs | Ambiguous, high-stakes, one-off decisions |
| No physical-world action needed | Physical dexterity / presence |
| Little human-trust requirement | Deep interpersonal trust & care |
Why "safe" is about autonomy, not intelligence
It's tempting to assume "smarter AI = fewer safe jobs," but the binding constraint in 2026 isn't raw capability — it's reliable autonomy. A model can draft brilliantly and still can't be left to own a consequential decision unsupervised. Work that requires being accountable for outcomes end-to-end is protected exactly as long as that autonomy bar stays unmet — which is what this scorecard tracks. See also will AI cause mass unemployment? and can AI replace knowledge workers?
How to know when the picture changes
The moment AI demonstrates reliable, unsupervised, end-to-end work — the drop-in-worker milestone — the "safe" map redraws fast. That milestone is the headline verdict on the AGI-2027 Thesis Tracker: one auditable score that moves the day the autonomy bar is cleared. It resolves by January 1, 2028.
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Frequently asked questions
In 2026, the most durable work needs reliable, unsupervised, end-to-end judgment, physical-world action, or deep human trust — the things AI still can't do reliably. AI automates scoped digital tasks (~83% GDPval) but can't own a whole job unsupervised, so task-bounded digital roles are the most exposed.
Task-bounded, fully digital, well-specified work is most exposed, because that's where AI's capability is strongest and the autonomy gap matters least. But 'replace' still overstates it — AI is automating tasks within jobs faster than it's replacing whole roles.
Because the binding constraint in 2026 is reliable autonomy, not raw intelligence. Work that requires being accountable for outcomes end-to-end, unsupervised, is protected as long as AI can't reliably do that — the exact gap the AGI-2027 verdict tracks.
When AI demonstrates reliable, unsupervised, end-to-end work — the drop-in-worker milestone behind the AGI-by-2027 verdict, which resolves by January 2028. The Thesis Tracker moves the moment that changes.
The live scorecard updates as models ship and verdicts change.
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The "safe jobs" map redraws when AI clears the autonomy bar. Subscribe to hear when it does. Free, no hype.
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