AI Job Value Index · 243 titles scored

What is your job titleworth in the age of AI?

Type any job title. You get a resilience score from 0 to 100, an honest read on what AI has already taken, and the specific moves that keep you valuable to the people who pay you.

Free · no sign-up · nothing stored. Follow Jonah to see this list as it shifts.

The two lists everyone asks for

Where the ground is collapsing — and where it is holding

Computed live from the same model that scores your title. Click any row to see the full breakdown and the way out.

Warning

The 20 worst jobs to hold right now

Highest automation exposure, lowest human moat. Several of these are not shrinking — they are finished.

Advantage

The 20 best jobs in the age of AI

Either you build the systems, or you do something that requires a body, a licence, or a human being who is accountable.

How the score is calculated

Every title is rated on five factors. The score is not a guess bolted on afterwards — it is computed from those five numbers, so the bars you see in your result are the actual arithmetic behind it.

Automation ExposureHow much of the core task set a current AI system already does end to end.
AI LeverageHow much AI multiplies this person's output instead of replacing them.
Judgment & AmbiguityDecisions with no clean right answer, made under real consequences.
Trust & AccountabilityWhether a named human must be answerable, licensed, or present.
Physical / Real WorldHands, bodies, sites, and messy environments that defeat software.
moat = 0.40·Leverage + 0.25·Judgment + 0.20·Trust + 0.15·Physical
score = clamp( moat − 0.55·Exposure + 25 , 0 , 100 )

Seniority adjusts the result: senior, lead and chief variants gain a few points for judgment and accountability, junior and assistant variants lose them — because AI removed exactly the tasks juniors used to learn on.

If your title is not in the dataset, the page estimates it from the words in it and says so plainly rather than pretending to certainty. Every figure and dataset this model is calibrated against is listed and linked below. This is an editorial model, not a forecast — it reflects how the value of a title is moving today, and it is deliberately blunt. Treat a low score as a prompt to move, not a prediction about you.

Where these numbers come from

The five factor ratings behind every score are an editorial judgment — mine, formed from working inside real AI deployments — and the arithmetic that turns them into a score is printed in full above. What follows is the published evidence those judgments are calibrated against, with every figure linked to its primary source.

The published evidence

  1. World Economic Forum — Future of Jobs Report 2025 Published January 2025 · survey of employers representing over 14 million workers Projects 170 million new jobs created and 92 million displaced by 2030 (net +78 million), and finds employers expect 39% of workers’ core skills to be transformed or outdated over 2025–2030. This is the basis for treating a job title as something that changes underneath you rather than disappears cleanly.
  2. International Labour Organization & NASK — Generative AI and Jobs: A Refined Global Index of Occupational Exposure Published May 2025 · 29,753 tasks mapped across occupations Finds that clerical occupations have the highest generative-AI exposure of any occupational group, confirming the 2023 index with stronger evidence, and that roughly one in four jobs worldwide sits in the exposed zone. This is why administrative and clerical titles dominate the bottom of the list on this page.
  3. U.S. Bureau of Labor Statistics — Employment Projections, 2024–34 Released August 2025 · official U.S. government projections Fastest declining: word processors and typists −36.1%, telephone operators −27.5%, switchboard operators −26.3%, data entry keyers −25.9%, telemarketers −22.1%, payroll and timekeeping clerks −16.7%, file clerks −15.9%. Fastest growing: wind turbine service technicians +49.9%, solar photovoltaic installers +42.1%, nurse practitioners +40.1%, data scientists +33.5%, information security analysts +28.5%.
  4. Brynjolfsson, Li & Raymond — Generative AI at Work The Quarterly Journal of Economics, vol. 140 no. 2, May 2025 (first circulated as NBER w31161) · 5,179 customer-support agents Access to an AI assistant raised productivity by 15% on average, with the largest gains going to the least experienced workers. This is the empirical spine of the AI Leverage factor — and the reason a high-exposure job is not automatically a doomed one.
  5. Hui, Reshef & Zhou — The Short-Term Effects of Generative Artificial Intelligence on Employment Organization Science, vol. 35 no. 6, November 2024, pp. 1977–1989 · natural experiment on a large online labour market After ChatGPT’s release, freelancers in the most affected occupations took 2% fewer monthly jobs and earned 5.2% less; the arrival of DALL·E 2 and Midjourney produced almost identical figures for design and image work (−2.1% jobs, −5.2% earnings). The paper also finds top-rated freelancers were hit disproportionately hard — being good at it was not protection. Direct market evidence for the low scores on copywriting, content and commercial design.
  6. Anthropic — The Anthropic Economic Index Ongoing · measured usage across millions of real conversations Rather than asking what AI could do, it measures what people actually hand to it, and splits that usage into automation versus augmentation by occupational task. Used here to sanity-check which tasks are genuinely being delegated today rather than in theory.

How this model holds up against the official projections

The scores on this page were not fitted to any of the data above, which is what makes the overlap worth showing.

Agrees on the declineEvery clerical occupation on the BLS fastest-declining list lands in this page’s bottom tier: typists and data entry keyers 0, file clerks 0, telemarketers 0, telephone and switchboard operators 14, payroll clerks 19, bank tellers 18.
Agrees on the growthBLS’s fastest-growing occupations are overwhelmingly physical or frontier, and score accordingly here: nurse practitioners 95, physical therapist assistants 94, wind and solar technicians 90, industrial machinery mechanics 90, information security 81.
Where it disagrees — read thisBLS projects data scientists +33.5%, among the fastest-growing occupations in America. This page scores Data Scientist 58. Both can be true: BLS counts headcount, this scores the durability of the title’s value, and routine analysis inside that title is being absorbed quickly even while the job category grows. Where the two disagree, the government projection is the harder evidence.

What this page is not

It is not a forecast, and it is not advice about you specifically — no model can see your employer, your market or what you are actually good at. It is a directional read on how the value of a title is moving, written to be blunt enough to act on. Scores are reviewed and updated as new data lands; the BLS figures are United States projections and will not map perfectly onto every labour market.

Nothing you type leaves your browser. The entire model runs client-side in this page — there is no account, no login, no database and no request sent anywhere when you score a job title.

Model version 1.0 · 243 titles · sources last verified 14 August 2026 · compiled by Dr. Jonah Tebaa, AI strategist and Co-CEO of Webspot.

A low score is not a verdict.
It is a deadline.

I help organisations and the people inside them turn AI from a threat into accountable capacity. If your role or your team is on the wrong side of this list, that is a solvable problem — but not by waiting.

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