AI career risk checker
See how exposed your role is to AI and what's actually driving your risk score
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How the checker thinks
Each tab below breaks down the logic behind your score so you can see exactly where it comes from and what it would take to shift it
Generally, jobs built around predictable, repeatable outputs—data entry, routine writing, document processing, basic analysis—tend to be more exposed. If most of your day-to-day can be described in a few steps, AI can likely handle a good chunk of it. The more your work depends on judgment, real accountability, or context that shifts constantly, the lower your risk tends to be.
Roles that involve real-time judgment, physical presence, or accountability that's hard to hand off tend to hold up well—think healthcare, skilled trades, complex negotiation, or anything with genuine ownership. If you're thinking about a pivot, moving toward roles with more decision-making, cross-functional scope, or client-facing complexity is generally a more durable direction than doubling down on tasks AI can already replicate.
AI tends to replace tasks before it replaces whole roles—and industries with heavy document workflows, standardized processes, or high digital volume often feel pressure first: finance, legal, media, customer service. Most jobs aren't going away overnight, but the parts of your work that are easiest to describe in a prompt are likely to shrink the fastest.
For white-collar tasks, change is moving faster than most people expect—though roles tied to physical presence or genuine accountability tend to shift more slowly. AI will likely create new kinds of work, though it won't automatically benefit everyone it displaces. People who start pairing AI tools with harder-to-replicate skills now tend to be better positioned for what comes next.
Skills that work alongside AI rather than compete with it—domain expertise, cross-functional judgment, stakeholder management, owning outcomes—tend to hold their value well. A useful way to think about future-proofing is shifting from executing tasks to directing them: deciding what's worth doing, checking what AI produces, and being the one accountable for the result.
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