Topper headline text

AI Career Toolkit
Free · no sign-up

Will AI change your job? Find out in 30 seconds.

Type a job title — the one you have, the one you had, or the one you are aiming for. You’ll get a score from published labor research, and what to do next.

  • Nothing to sign up for
A Merit America alumna working at a laptop
How it works

How this calculator works

1

Type your job

We match it to one of 800-plus standardized U.S. occupations.

2

We pull your score

Every occupation carries a fixed exposure score from published labor research, not a guess and not AI-generated.

3

You get a next step

We show what your score means and the Merit America track that builds durable, in-demand skills.

Scores combine two peer-reviewed studies: the AI Occupational Exposure index (Felten, Raj and Seamans, 2021) for knowledge and office work, and the Oxford computerisation study (Frey and Osborne, 2013) for hands-on and routine work. We report the higher of the two, so a role counts as exposed if either lens flags it. Exposure measures how much AI could change the tasks in a job. It is not a prediction that the job disappears.

Tasks, not titles

What actually moves your score

Your job title is not what gets scored. Your tasks are. AI takes over some kinds of work fast and stumbles on others, so two people with the same title can land in very different places.

Easier for AI
Routine steps that repeat the same way
Predictable, rule-based decisions
Sorting and processing information on a screen
Work that follows a fixed script
Harder for AI
Hands-on work in messy, changing conditions
Judgment when the data is thin
Trust, care, and reading people in the room
Framing new problems, not just answering old ones
What AI can’t copy

The skills that stay in demand

Exposure is not destiny. The people who get ahead pair what they already do with the skills AI cannot replicate.

Human connection

Building trust, reading a room, and handling the moments that need a real person. AI can sound warm, but it does not feel.

Judgment in the gray areas

Making the call when the data runs out. Weighing trade-offs and deciding what actually matters.

Original thinking

Coming up with the new idea, not the average of old ones, and asking the right question in the first place.

Two Merit America alumni working through something together at a laptop

Communication that lands

Turning something complicated into something people can act on, and bringing them with you.

Working with AI

Knowing what these tools do well, where they fall short, and when to trust your own read instead.

Skill categories drawn from Harvard Business School Online’s research on human skills in the age of AI and Harvard economist David Deming’s work on the rising value of social skills.

Knowing which skills hold up is the easy half. The harder half is getting an AI tool to actually help you build them. That is the next two steps, about seven minutes, and it is the difference between a generic answer and a useful one.