AI Job Risk Calculator

Our calculator is a tool you can use to get an idea of how likely a job is to be impacted or altered by AI in the next few years.

Our calculator considers the occupation’s structure, the job’s responsibilities, the work context, the skills you need, the activities you perform, salary, how the work is done, where you are located, and your experience.

Importantly, the point isn’t to guess if a job will vanish. It’s to estimate how much of the job AI can take on, which parts can be automated, what requires a human touch, and how quickly AI might start changing things. This approach provides a more sensible view of how AI impacts jobs and the question everyone is asking: “Will AI take my job?”

Why most AI job risk discussions are oversimplified

Nowadays, many reports discussing which jobs are at risk from AI are too simplistic, focusing mostly on jobs as a whole. But a job isn’t just one thing. Most jobs involve some work that is very easy to automate, some that can be partially automated, and some that absolutely need a person.

For instance, an accountant might spend some of their day putting together and reconciling structured financial data (this is very exposed to AI), but will also be investigating inconsistencies, communicating with regulators, and making ethical decisions (AI is less likely to do these). Similarly, a teacher might use AI to help create lesson plans, but helping students who are struggling will always require a human. And a software developer may increasingly use code generated by AI. However, they will still be responsible for designing the overall system and turning a business’s needs into a technical solution.

That’s why, with our AI job risk calculator, we’ve decided to focus on what a job is made of, rather than just give a binary answer: AI will replace your job vs. AI cannot replace your job.

Our AI job risk calculator is more than simple to use. You simply need to select the following info:

1. First, your yole: The job you do is the starting point — the calculator uses information from O*NET (a standard for occupational data). The list includes jobs such as accountants, software developers, teachers, nurses, truck drivers, marketers, writers, and customer support staff, among others.

2. Second is your experience level: Are you a junior/entry, mid-level, or a senior/lead? This input is important because more experienced people tend to take on more strategic roles, coordinate with others, lead, and exercise judgment. Whereas entry-level jobs generally involve more work that’s done the same way each time, is procedural or standardized, and is therefore easier to automate.

3. Then, your annual salary is also taken into consideration. The calculator uses your pre-tax salary from the Occupational Employment and Wage Statistics program of the U.S. Bureau of Labor Statistics (2022). Your salary also gives a clue to how likely AI automation is: if it costs a lot to employ someone, companies have more reason to invest in AI. It compares your salary to the median for your job to estimate how likely a business is to use AI to handle some of your work.

🙋 Want to calculate your annual salary? Head over to our hourly to salary calculator!

4. The country and geography you’re in matter too. AI is being adopted at very different speeds in different places. The calculator uses OECD regional AI exposure research to estimate whether the economy where you are will accelerate or slow AI adoption. You’ll choose your country, then the type of area you’re in: rural/low-tech, standard, or tech hub/major city. Big, technologically advanced cities tend to get AI systems quicker than rural areas.

5. Lastly, the calculator asks about your work mode: Are you remote, hybrid, or on-site? Increasingly, recent studies from UCLA Anderson (Schubert, 2025) show that remote work, which is done (obviously) on computers, is more likely to be changed or automated by AI because the work is already digital, you communicate using software, and it’s easier to automate what you produce. Work that’s done in person often involves more unpredictable things in the real world and dealing with people. Researchers from the OECD and the IMF came to the same conclusion.

6. And that’s it! The “how will AI affect jobs” calculator then generates:

   • An AI exposure level;
   • Estimated transformation timelines;
   • The main AI exposure driver;
   • The main protective factor; and
   • A task composition breakdown.

Pretty nice, right?

The methodology behind the AI job risk calculator is based primarily on O*NET occupational datasets, as we’ve said above, combined with external research on AI exposure (which you can find in the sources of this article). So first of all, we used four major O*NET taxonomies:

• Skills;
• Work activities;
• Work context; and
• Tasks.

Then, for each dataset, we categorized occupational elements into six AI-related dimensions, as follows:

1. Digital and software work: These are tasks involving computers, software, digital systems, databases, coding, online tools, or digital workflows.

   For example, emailing, managing databases, data entry, coding, using a CRM, analyzing spreadsheets, etc.

   → These tasks are generally highly exposed to AI systems.

2. Analytical and knowledge work: These are tasks involving reasoning, research, writing, understanding, interpretation, analysis, planning, or making decisions.

   For instance, financial analysis, legal research, strategic planning, content writing, and market analysis.

   → Recent advances in large language models (LLMs) have dramatically improved AI performance in such skills and tasks.

3. Repetitive and structured tasks: These are tasks involving rule-based work following predictable procedures, etc.

   For example, processing invoices, providing standardized customer support, filling out forms, scheduling routine tasks, and preparing regular reports.

   → These are the most likely to be automated.

4. Human interaction: These tasks require empathy, negotiating, teaching, building relationships, emotional intelligence, or trust.

   For instance, counseling patients, resolving disputes, mentoring in a classroom, and calming down a customer.

   → These are currently quite safe from AI.

5. Management and strategy: This involves leadership and organizational coordination work.

   For example, supervising teams, deciding what’s important, making strategic decisions, planning the organization, and running things at a high level.

   → AI can help with leadership, but people are still needed for responsibility and judgment.

6. Physical and manual work: These tasks involve performing real-world activities that require physical effort.

   For example, fixing machines, plumbing, electrical work, moving patients, warehouse logistics, and physical navigation.

   → While robotics continues to improve, real-world physical environments remain significantly harder to automate than purely digital workflows because they require movement precision, environmental adaptation, and real-time sensory interpretation.

For each O*NET element, we calculated weighted scores using O*NET importance values. Thus, we mapped each skill, activity, work environment, and actual task to one of the six categories. So, for instance:

• “Sending emails” contributes to “Digital and software work”;
• “Negotiating with customers” contributes to “Human interaction”;
• “Operating machinery” contributes to “Physical work”; and
• “Coordinating employees” contributes to “Management and strategy”.

Then we added up all these scores for skills, activities, work environment, and tasks:

• “Digital and software work”, “Analytical and knowledge work”, and “Repetitive and structured tasks” were considered the main drivers of AI’s impact on a job.
• “Human interaction”, “Management and strategy”, and “Physical and manual work” were seen as ways to lessen the AI impact.

How we built the final AI exposure levels

The calculator combines:

• AI exposure drivers (how likely a job is to be changed);
• Protective factors (how protected it is from AI);
• Economic modifiers; and
• Regional adoption indicators (how quickly AI is being adopted in a particular region of the world).

We normalized the final results and then calibrated our scores using the ILO 2025 Refined Global Index. The ILO found that no job is truly 0% or 100% automatable. That’s why we normalized our index: to reflect these exposure gradients. This method aligns with what the International Labor Organization (ILO), OECD studies on AI exposure, and research on automation at the job level also show. The final model assigns points to low, moderate, high, and very high exposure levels, and these thresholds help us estimate how long it will take for AI to transform a job.

How we built the estimated timelines

One of the most common questions people ask is: “What jobs will AI replace by 2030?” Well, our calculator does not tell you that; instead, we built it to add nuance to a conversation often dominated by absolute certainty. So you need to bear in mind that the timelines are not predictions of full job replacement. Instead, they estimate when AI tools may begin meaningfully restructuring workflows, reducing demand for certain tasks, or changing how the occupation operates. These timeline estimates are influenced by task digitization, current AI capabilities, labor cost incentives, regional adoption rates, and observed enterprise AI deployment trends.

The calculator generates 3 scenarios with a respective timeline:

• Fast AI adoption;
• Expected AI adoption; and
• Slower AI adoption.

Why task-level analysis matters

Looking at the individual tasks within a job is important. Most discussions about automation skip over what the job actually involves. We haven’t.

We analyzed task-level data from O*NET, focusing on the importance, frequency, and relevance of each task. This allowed us to work out how much of the job is digital, analytical, repetitive, people-focused, management-focused, or physical. The calculator then shows this visually in a task breakdown pie chart at the bottom once all fields are filled in. This approach helps people see which parts of their job are most at risk from AI and which are likely to be more stable.

No one can really answer the question “What jobs will AI replace by 2030?” or predict mass unemployment. Instead, we can focus on which jobs AI will replace (or rather may replace), for instance, in terms of task share.

In general, jobs that involve a lot of repetitive digital processes, handling structured information, standardized communication, or working according to strict rules are most at risk. By 2030, McKinsey Global Institute projects that activities accounting for up to 30% of hours worked in the US could be automated. This often includes jobs such as:

• Data entry keyers;
• Telemarketers;
• Customer support specialist;
• Data analysts; or
• Administrative clerks.

However, Goldman Sachs research provides a crucial nuance: while AI might displace some tasks, it also creates new job categories.

No job is totally safe from AI. However, some jobs are more protected because they require a lot of trust, understanding others’ feelings, physical adaptability, leadership, creativity, or moral judgment. Such jobs often include:

• Therapists;
• Nurses;
• Teachers;
• People in skilled trades;
• Emergency responders;
• Leadership-heavy roles.

An interesting shift, however, is happening concerning these kinds of jobs. People are starting to relate to areas like medicine and therapy in a new way. In fact, recent research shows that more and more of us are asking AI for medical guidance or even using chatbots to try to deal with emotional problems ourselves.

Though AI can give you answers quickly or simple ways to manage feelings, it doesn’t pick up on the subtle, complex signals of someone who is really struggling.

❗ If you’re worried about your health or mental well-being, getting advice from a qualified professional is the safest, most appropriate thing to do.

What happens with work in the future seems very uncertain at that moment. But hopefully, it won’t just be about artificial intelligence taking people’s jobs. Based on various research and studies, it seems that AI will involve reorganizing how work gets done, redistributing tasks, helping/augmenting employees, and, yes, fundamentally altering how people used to contribute.

So the main thing we should be asking isn’t only “Will AI take my job?” but also: which specific parts of my job are in danger, what abilities will keep me employable, how rapidly my field is transforming, and what I can do to manage those changes.

Even though we can’t predict the future, the AI job risk calculator is meant to give people a clearer, task-by-task, fact-based way to think about these issues.

💡 Plan your growth and see how your income might evolve with our future salary calculator.