Will AI replace your job?

Pick a role and see which parts of the work are most exposed to AI, which parts still depend on human judgment, and what would be worth learning next.

Pick your role — UX Designer and Software Engineer are live now; more are on the way.

No account needed. The free reports show the score, the task split, the human moat, and the sources behind the estimate.

Based on task-level occupational research — O*NET · ESCO · ILO · OECD · OpenAI/OpenResearch · Anthropic Economic Index · Microsoft Research · BLS · WEF.

Sample reportView full report →
UX Designer
Watch first: Research synthesis & first draftsHuman moat: Product judgment
58
Significant AI task exposure

Start with the closest match.

Job titles are messy. Pick the role that feels nearest, then read the task breakdown rather than treating the title as exact.

The score is about work, not fate.

A higher number means more of the day-to-day work is easy for AI to speed up or standardise. It is not a layoff forecast.

Look for the next move.

The useful part is the split: which tasks get cheaper, which tasks still need you, and what skill gap is worth closing first.

How it works

From job title to survival map

01
Pick the nearest role

Choose the role that best matches your work. The report is more useful when you read it through the tasks, not the title alone.

02
It is matched to task data

Roles are tied back to occupational task statements from sources such as O*NET and ESCO.

03
Each task is scored

The model weighs routine work, digital work, language work, judgment, human interaction, and physical-world dependency.

04
You see what changes

The report shows exposed work, protected work, source confidence, and the first skills worth building.

The model

Job risk is made of five layers

Exposure is highest at the top — routine, screen-based work — and lowest at the base, where presence, trust, and judgment live.

Routine digital tasks
Writing & information tasks
Decision complexity
Human interaction
Physical-world dependency
More exposed to AIMore protected
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Transparent by design

No black box. The formula is public.

Every score is a published heuristic built from credible occupational data, with confidence levels and limitations shown on every page.

Read the methodology →
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