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How do I measure AI exposure?
Short answer
Measure AI exposure by decomposing the role into tasks, judging each task against what AI systems can currently do, weighting by how much of the week each task takes, then aggregating to a role-level score. Scoring the job as a single unit produces unreliable results, because exposure varies sharply between activities inside the same title.
Last updated 14 September 2026 · JobsAIQ Research
The three exposure categories
| Automatable | AI completes the task end to end with light review. |
|---|---|
| Augmentable | AI produces a first pass; a person directs, corrects and decides. |
| Resistant | The task depends on presence, accountability, negotiation or context AI cannot reach. |
Scoring your own week
- List tasks with time shares that add to 100.
- Assign each a category.
- Weight automatable heavily, augmentable moderately, resistant lightly.
- The weighted total is a rough 0-100 exposure reading.
- Sanity-check it against how postings for your role are being written.
Run the scan and see this applied to your own role rather than the average.
Why research-grounded scoring is better
Self-assessment is a good starting point but it is biased - people tend to over-rate the defensibility of their own work. Grounding the score in occupational task data and published exposure research reduces that bias, which is how JobsAIQ produces the AIQ Score.
Frequently asked questions
- Is exposure the same as risk?
- No. Exposure is how much AI can do. Risk depends on employer decisions and market conditions on top of that.
Your next move
Check your AI Career Intelligence.
Get your AIQ Score, the exposure behind it, your strengths, your skill gaps and a 14-day plan - built from your own profile, not an industry average.
- Takes about 4 minutes
- Your CV stays private
- Score, report and roadmap