JobRiskAI

Will AI take your job? Read the data, task by task.

Below, every dot is one of 785 real occupations, placed by its measured overlap with what AI actually does today. Find yours, see which of your tasks AI can and cannot do, and leave with a plan. No doom meter. No fake precision.

785 occupations covered. Job title not on the list? Assess it from your actual tasks

785occupations scored, from chief executives to roofers
332work activities measured for real AI usage and success
200,000anonymized AI conversations behind the scores
The field of work hover a dot to name it · click to open · or search above

Jobs don't get automated. Tasks do.

Every serious study since 2013 lands on the same point: a job is a bundle of tasks, and AI takes over some of them while leaving others untouched. That is exactly how this site measures risk.

  1. Your job becomes its activities

    Each occupation is decomposed into the work activities that actually fill its week, weighted by importance, using the U.S. Department of Labor's O*NET framework.

  2. Each activity gets a measured value

    Microsoft Research measured how often AI is really used for every activity, how successfully it completes it, and how much of it AI covers. Observations, not predictions.

  3. The overlap becomes your move

    You see which of your tasks overlap with AI and which don't, adjust the estimate for how you personally work, and leave with a concrete plan: what to shift toward, what to own, what to learn.

Where 785 occupations actually land

Bands are quintiles of the measured score distribution, so each band holds one fifth of all occupations. A band tells you where you stand relative to everyone else, not a percentage chance of losing your job. Nobody can honestly give you that number.

High
Elevated
Moderate
Low
Minimal

The edges of the distribution

Highest AI applicability

    Lowest AI applicability

      Browse and filter all 785 occupations  ยท  Compare any two side by side

      High exposure is not a pink slip

      Exposure means overlap, not replacement. A high score says AI can already do meaningful parts of your job's activities. History says that cuts both ways: ATMs didn't eliminate bank tellers for decades, they changed what tellers did. Anthropic's usage data shows AI augmenting people (52% of use) slightly more often than automating work outright (45%).

      The labor market is churning, not vanishing. The World Economic Forum's 2025 employer survey projects roughly 92 million jobs displaced and 170 million created by 2030. The IMF estimates about 40% of jobs globally are exposed to AI, and stresses that roughly half of those may be complemented rather than replaced.

      But "someone using AI" is a real threat. The consistent pattern across studies: the near-term risk isn't a robot taking your seat. It is a person in your field who uses AI well, producing two or three times your output. Exposure data tells you exactly which of your tasks that person will accelerate.

      That is why every page here ends with a plan. Which tasks to hand to AI first, which human-anchored tasks to double down on, and which adjacent roles share your skills with less exposure. All of it computed from real activity overlap, not vibes.

      Job title not on the list? Freelance? Hybrid role?

      Build your exposure profile from what you actually do all day: ten task families, measured against the same activity data.

      Assess your tasks

      Questions people actually ask

      Is this "AI-powered"? What actually computes my result?

      No model runs when you use this site, and nothing you type leaves your browser. The scores were computed by Microsoft Research from 200,000 anonymized Bing Copilot conversations and published openly (CC BY 4.0). We turn that dataset into readable, task-level pages and transparent arithmetic. Every step is documented on the methodology page.

      Does a high score mean I'll lose my job?

      No. It means AI can already perform meaningful parts of your occupation's activities, which historically leads to job redesign, wage pressure on routine work, and advantage for people who adopt the tools early. Displacement is one possible outcome among several, and the studies that predicted mass unemployment on a timetable have so far been wrong.

      Why should I trust this over other "will a robot take my job" sites?

      Three reasons. First, the data is measured usage, not a 2013-era expert guess about "computerisation probability." Second, we show our work: every occupation page lists the underlying activities and their measured AI overlap. Third, we never print fake precision. You get bands, percentiles and ranges with stated limitations, not "87.3% doomed."

      Is my data collected?

      No accounts, no cookies, no tracking scripts, no analytics beacons. Quiz answers are processed in your browser and go nowhere. The one optional convenience, the "recently viewed" list, lives in your browser's local storage and never leaves your device.

      My country isn't the U.S. Does this apply to me?

      The occupation taxonomy and activity weights are U.S.-based (O*NET), but the task content of an accountant's or nurse's day is broadly similar across developed economies, and the AI usage data itself is global. Treat the score as a task-exposure signal, not a national labor-market forecast. Local regulation, wages and language markets shift the timeline.

      How current is the data?

      Scores come from Microsoft Research's 2025 "Working with AI" study, the largest published task-level measurement to date, joined with the O*NET 30.0 database (2025). We revisit the sources and refresh when materially better data is published. The current data vintage is always listed in the methodology.