How exposed is your role to AI?
Look at your actual week, task by task. See what AI is likely to take on, what it will help with, and the experience that keeps you valuable.
How it works
Your role and week
Pick your role and level, tick the tasks you really do, and say roughly how much time each takes.
Task by task
Each task is rated Routine, Assisted or Context-heavy, the same task-by-task approach used by the International Labour Organization’s research on AI and work.
What keeps you valuable
See the judgement, accountability and know-how that carry into an AI and data-led future.
AI and your job: common questions
Will AI take my job?
For most people, AI is more likely to change their job than replace it. The International Labour Organization’s 2025 study found that about one in four workers worldwide are in jobs with some exposure to generative AI, and that most of those jobs are more likely to be transformed than replaced, because they still include tasks that need a person. What usually changes is the mix of tasks in your week. That’s why this check looks at your tasks, not just your job title.
Which jobs are most exposed to AI?
Jobs with a lot of routine information work, such as data entry, administration, bookkeeping and parts of customer service. The ILO found clerical work has the highest exposure of any group. Within any job, exposure depends on how much of the week goes on tasks that follow the same steps every time.
Which jobs are safest from AI?
No job is completely untouched, but work that depends on judgement, trust, care, accountability and local know-how is the hardest to automate. Nursing, social work, teaching and management all lean this way. Most roles are a mix, and this check shows yours.
What does my AI exposure score mean?
It’s the share of your week spent on routine tasks AI can largely do, plus half the share spent on tasks AI can speed up while a person checks. It is not the chance of losing your job. A higher score means more of your week is likely to change, so it’s worth planning where your time and skills go next.
How is AI exposure measured?
Researchers break jobs down into tasks and rate how much each task could be done or sped up by AI. This check uses the same task-by-task approach as the ILO’s research and the 2023 study by Eloundou and colleagues, which estimated that about 80% of US workers could see at least 10% of their tasks affected by large language models.
Is it free, and what happens to my answers?
It’s free, with no sign-up. Your answers are saved only in your own browser so you can come back to them. They aren’t sent to us, and “Clear my assessment” deletes them.
How can I move into an AI or data role without starting over?
Most successful moves build on the experience you already have: a finance professional moving into finance data analysis, an HR adviser into people analytics, a nurse into health informatics, an administrator into operations and automation. Start by making your human strengths visible, then learn the tools that fit your area. Quaverix’s Career Pivot Blueprint maps the route for you.
AI Exposure Check
Your AI Exposure Check result
Check again in six months
AI tools change quickly, and so does your role. Set a reminder to retake the check and see what has moved.
The part of your work AI can't take
Would you like to move into an AI or data‑led version of your role, without starting over?
The right move depends on more than your job title. It depends on how you think, solve problems, learn and communicate, and on the experience you've already built.
No problem. Your result stays on this device until you clear it. You can share it, or check another role below.
The Quaverix Career Pivot Blueprint
Your score shows how much of your week is human work. The Blueprint shows where that experience fits best in an AI or data-led role, and how to get there.
- Take a 15-minute assessment. Questions about how you think, learn and work, plus your experience.
- Get your personal report in minutes. Around 20 pages, on your dashboard and as a PDF.
- Follow your plan. A practical roadmap, phase by phase.
Not ready yet? Start with Quaverix's free tools:
- Free ATS CV checker · no account needed
- CV Builder with ATS scoring · free account
- Salary reference · free account
- Your AI career readiness score and professional archetype
- Your transferable strengths and skills-gap snapshot
- AI and data career paths that fit how you solve problems
- Salary insights for those paths in your country
- Personalised learning recommendations
- A practical, month-by-month transition roadmap
- For a limited time: 12 months of the LinkedIn Profile Enhancer and Interview Preparation tools
Quaverix makes this tool and the Blueprint, which is a paid product. No report can guarantee a job, offer or salary; it gives you a clearer, evidence-based starting point.
How your score is worked out
Each task is rated using the R-A-C method. Routine tasks follow the same steps each time, and AI can do most of them today. Assisted tasks can be sped up or drafted by AI, but a person checks and steers. Context-heavy tasks depend on judgement, relationships, accountability or knowledge that isn't written down.
Your score is the share of your week on Routine tasks, plus half the share on Assisted tasks. Context-heavy tasks add nothing. Time is estimated from your answers: a little ≈ 5%, some ≈ 20%, a lot ≈ 40%, most of my week ≈ 60%, then scaled to 100%. Bands: 0–29 Low · 30–54 Moderate · 55–74 High · 75+ Very high.
The typical score for a role assumes someone does every listed task for that role and spends equal time on each. Your answers about judgement, accountability and know-how shape the "what keeps you valuable" section, not the score.
The research behind the method
We use the same task-by-task approach as leading research on AI and work:
- The International Labour Organization's 2025 global index of exposure to generative AI found that about one in four workers worldwide is in a job with some exposure, that clerical work is the most exposed, and that most jobs are more likely to be transformed than replaced, because they include tasks that need human input. (Gmyrek et al., ILO Working Paper 140)
- Earlier research estimated that around 80% of US workers could see at least 10% of their tasks affected by large language models, and about 19% at least half. (Eloundou et al., 2023)
Our task ratings are Quaverix's own assessments, checked for consistency with this research: as in the ILO's findings, clerical roles such as data entry and bookkeeping have the highest typical scores, and management and advisory roles the lowest. This tool does not use official ILO or other published scores.