Is my job safe from AI?

Nobody can give you one honest percentage for that, and LEXUN refuses to invent one. What it can do is walk through the components that actually determine exposure — how routine your tasks are, how much of your work needs physical presence, judgement or accountability — and show you the reasoning, clearly labelled as reasoning support rather than a prediction.

What jobs are most at risk from automation?

LEXUN does not publish a ranked list of doomed professions, because no verified occupation-level dataset is connected and a ranking without one would be theatre. Exposure differs more between tasks than between job titles: the same title can be heavily exposed in one workplace and barely touched in another, which is why the checker asks about your tasks, not your title.

How do I check my automation exposure?

Answer the checker's questions about your actual work — routineness, physical presence, judgement, accountability, how your output is checked. The headline you get is earned from those components and shown with them, so you can disagree with any step. It is deliberately qualitative: a number here would masquerade as measurement.

Tool · Automation exposure

LEXUN Labs · experimental tool, outside the released models

Is my role exposed to automation?

Anyone who gives you a single scary percentage for this is making it up. Exposure works at the level of tasks, not job titles — and being exposed is not the same as being replaced. This check looks at your task mix honestly, tells you which parts carry exposure, and what to strengthen.

How this works (and its limits): your answers feed a transparent rule-based assessment — no model pretends to know your employer, your sector's pace, or the economy. It produces a qualitative reading of your task mix, never a probability of losing your job. Nothing you enter leaves your browser, and nothing is saved anywhere — not even on this device — unless you press “Remember this assessment” afterwards.

Your task mix

How much of your week is routine information processing?

Drafting standard documents, data entry, summarising, formatting, processing forms — the tasks current AI systems do most readily.

How often do you make judgment calls with real consequences?

Decisions where being wrong costs money, safety or trust — and where someone must be accountable. Accountability resists automation strongly.

How central is in-person human contact to your work?

Care, negotiation, teaching, physical presence with clients or patients — tasks where the human is the point.

Does your role need skilled physical work in unpredictable places?

Trades, repairs, care, field work — robotics still struggles far more with a boiler cupboard than with paperwork.

Are you the person who decides how new tools get used, or the person they get applied to?

People who direct the tools tend to absorb automation as leverage; people whose output the tools reproduce feel it as pressure.

Your automation-exposure reading

Most protected parts of your week:

Worth strengthening this year:

Rule-based reading of your stated task mix — not a prediction about your employer or a probability of job loss. Re-check if your task mix changes materially, or yearly.

Model the finances of a move → Read the career-change guide

Exposure is not replacement

Task exposure means parts of your work can be assisted or produced by automation. Replacement needs much more: the economics to favour it, your organisation to act on it, regulation to allow it, and customers to accept it. High exposure with strong judgment, accountability and human-contact tasks usually means your role changes shape rather than disappears — and the people who direct the new tools usually end up ahead.

What no honest tool can tell you: your employer's plans, your sector's pace, or a percentage with your name on it. What you control is your task mix — and whether a financial buffer exists if you choose to move. That second question is exactly what the career model answers, with real maths.