What This Calculator Is Really Measuring
Behind the single percentage is one simple idea: the more of your day that runs on routine, predictable steps, the more of it an automation lens flags as exposed. Work that leans on judgment in messy situations, physical dexterity, or genuine human connection sits on the resilient side of that line. So the calculator does not try to read the future of your specific job — it reads the shape of your tasks and turns it into an illustrative score you can reflect on. Think of the number as a mirror for your daily work, not a crystal ball for your paycheck.
How Task Mix Drives the Score — A Worked Example
Picture two people who both call themselves marketing coordinators. The first spends the day pulling numbers into the same weekly report, reformatting spreadsheets, and answering routine inbox questions from a template. Almost all of that is repetitive and predictable, so the automation lens scores it as heavily exposed. The second coordinator spends the day pitching skeptical clients, reading the room in a tense meeting, and inventing a campaign angle nobody has tried. Those tasks lean on trust, creativity, and judgment, so the same tool returns a much lower score. Identical title, very different results — because the calculator is watching what fills the hours, not the name on the badge.
A Speculative Estimate, Not a Prophecy
It is worth saying plainly: this score is an educated thought experiment, not a prediction that anyone will lose their job. It cannot see your employer, your reputation, your local job market, or the countless ways a role gets rebuilt rather than erased when new tools arrive. History leans toward jobs changing more often than vanishing outright. Read a high number as an invitation to get curious about your task mix and think about what to learn next — not as a countdown clock.
AI Job Displacement Calculator
Estimate how AI and automation may affect your occupation over the next 5-10 years based on task composition and AI capabilities.
AI Displacement Risk by Occupation (2026 Estimates)
Based on task composition analysis and current AI capabilities
| Occupation | 5-Year Risk | 10-Year Risk | Primary Threat | Outlook |
|---|---|---|---|---|
| Data Entry Clerk | 72% | 89% | LLMs + RPA | Very High Risk |
| Software Developer | 18% | 35% | AI Coding Tools | Moderate (Augmentation) |
| Registered Nurse | 5% | 12% | Minimal | Low Risk |
| Truck Driver | 8% | 28% | Autonomous Vehicles | Growing Risk |
| Financial Analyst | 35% | 55% | LLMs + Analytics AI | High Risk |
| Electrician | 3% | 8% | Minimal | Very Low Risk |
| Customer Service Rep | 55% | 75% | Chatbots + LLMs | Very High Risk |
How to Use This Calculator
- Pick Your Occupation: Choose the occupation that best matches your day-to-day work. This anchors the estimate before the finer details refine it.
- Add Context About Your Work: Fill in education, years of experience, and industry. These shift the baseline up or down, since the same kind of task looks different across fields and career stages.
- Choose Your Primary Task Type — Carefully: This is the field that moves the score the most. Be honest about how routine your typical day really is versus how much rests on judgment, dexterity, or human connection.
- Read the Result as a Prompt: Look at the 5-year and 10-year bands and the task-automation share, then use them to reflect on what to learn or rebalance — not as a verdict on your job.
How It Works
Give the calculator your occupation, education, experience, industry, and — most importantly — the kind of work that fills your day, and it returns an illustrative exposure score for the next 5 and 10 years. The engine leans hardest on your task mix, because that is what actually decides how automatable a job is. A role built on routine, predictable steps scores higher than one built on judgment, physical dexterity, or genuine human connection.
The basic rule:
- Task type carries the most weight. Routine cognitive work — data entry, form processing, scheduling, first-pass document review — is the easiest for today's AI to imitate, so it lifts the score the most.
- Skilled physical work and relationship-heavy work pull the score down. Wiring a panel, setting a fracture, or talking a client off a ledge all demand real-world dexterity and trust that software cannot fake.
- Mixed roles land in the middle. If only part of your day is routine, only that part is exposed, and the number reflects a blend rather than an all-or-nothing verdict.
- Experience nudges the score toward resilience. Longer track records usually mean more of the judgment and context that are hard to automate and easy to redeploy alongside AI tools.
Read the result as a conversation starter, not a countdown. It reflects how routine your described tasks look to an automation lens on one particular day, using rough assumptions about where AI stands. It has no way to know your employer, your local market, or how your role will be redrawn as tools change. Two people with identical inputs can end up in very different places depending on what they choose to learn next.
Tips & Considerations
- Spend your effort on the primary task type field — it drives the score more than any other input, so an honest answer there matters most.
- Try the calculator twice: once for a routine-heavy version of your day and once for a judgment-heavy version, and watch how far the number moves.
- If your work is genuinely mixed, pick Mixed rather than forcing it into one bucket — the blended score is closer to reality.
- Compare the 5-year and 10-year bands as a sense of direction, and remember the longer horizon carries more guesswork.
- Let a high score point you toward skills the tool treats as resilient — judgment, creativity, dexterity, and human connection — rather than toward panic.
Frequently Asked Questions
What actually makes a job automatable?
Predictability and repetition. When a task follows the same steps on similar inputs and success is easy to check — sorting records, filling standard forms, drafting boilerplate, answering common questions — software can learn the pattern and repeat it cheaply. What resists automation is the opposite: judgment under uncertainty, physical dexterity in messy environments, and work that depends on human trust and connection. That is why the calculator asks about your primary task type before anything else.
Is this score a real prediction that I'll lose my job?
No. It is a speculative, educational estimate, not a forecast about you or anyone else. It looks at how routine your described tasks are and turns that into an illustrative exposure number. It cannot see your specific employer, your performance, your local economy, or the ways your role may be reshaped rather than removed. Treat a high score as a prompt to think and plan, not as a verdict.
How is the 5-year number different from the 10-year number?
The 5-year figure reflects tasks that current or near-term tools can plausibly take on. The 10-year figure stretches further, allowing for capabilities that do not exist yet and for slow-moving adoption to catch up. The longer horizon is inherently fuzzier — the wider the window, the more guesswork sits inside the number — so treat the gap between the two as a rough sense of direction, not precision.
How do I future-proof my career against AI?
Lean into what the automation lens scores as hard to replace. Get fluent with the AI tools in your own field so you direct them instead of competing with them. Deepen skills that need judgment, creativity, or human rapport. And shift your time toward the parts of your work where a person deciding and a person being trusted still matter. You do not need to abandon your field — usually you can rebalance your task mix within it.
Why did two similar jobs get very different scores?
Because the calculator weights what you do far more than your title or salary. Two people can share a job title yet spend their days differently — one buried in routine processing, the other in client relationships and edge-case decisions. Change the primary task type and you will see the score move sharply, which is the whole point: it is the task mix, not the label, that drives exposure.
Does more education mean a lower score?
Not automatically. Plenty of desk-bound knowledge work is highly routine and scores as quite exposed, while hands-on skilled trades score low. Education helps mostly through adaptability — it tends to make it easier to move into new tasks and pick up new tools. What protects a career is the shape of the daily work plus a willingness to keep learning, not the diploma on its own.