If AI Is Changing Your Role, Start Here.

This is a companion to a recent piece we wrote on the people question inside every AI strategy. That piece was for leaders. This one is for the person inside the question.

If you have been told that your role is changing or going away because of AI, or you can feel it shifting under you even before anyone says it out loud, this is for you. The point of this piece is to give you a place to start, when starting is the hardest part.

You are not obsolete.

A role can change. A task can be automated. An organization can decide it needs a different operating model. None of that erases your judgment, your experience, your relationships, or your ability to learn what comes next. It does mean the next chapter is going to take a little planning.

If you have already spent the last two years learning new tools or helping your team through change, that work was not wasted. It also does not guarantee protection from restructuring, which is part of what makes this moment so hard.

Step one: get specific about what is changing.

“AI” is too broad to act on. The first useful move is to look at your own work and figure out what is shifting. Not the headlines about your industry. Your work. The reports you write. The meetings you run. The decisions you make. The people you support.

Take the things you do in a typical week and put each one into one of three buckets.

• Tasks AI excels at
• Tasks AI can help with, where your judgment still matters
• Tasks that depend on trust, context, relationships, or accountability

That third bucket tends to be larger than people expect. It is also where most of your value sits. Knowing what is in it gives you something concrete to talk about, with your manager, with a recruiter, or with yourself.

Sorting your work this way is harder than it sounds, especially if the change has been sudden. Take it in pieces.

Step two: think carefully about retraining.

There is good news in the data. A 2025 working paper from the National Bureau of Economic Research looked at people whose work was most exposed to AI and found that retraining produced real earnings returns, around $1,470 per quarter on average. That shows up in paychecks after the training is done (Hyman, Lahey, Ni, and Pilossoph, NBER, 2025). The workers in that study went through federal training programs, the same kind we point to in step three.

The wrinkle is worth knowing. The same study found that workers who pursued more general training did better than workers who tried to retrain specifically into AI-intensive jobs, by about 29 percent. Chasing the most AI-heavy roles is not always the smartest path.

“Learn AI” is a slogan, not a plan. A better question is which skills you already have that transfer well into the work that is growing, and what would take you a few months to add. The strongest moves we see are usually adjacent, not radical.

Step three: use the resources that already exist.

Most people in this situation try to figure it out alone. More help is available than people realize, most of it free.

In the U.S., CareerOneStop, run by the U.S. Department of Labor, has a skills matcher, training and certification options, local job-center support, and tools for thinking about a career change. It is practical and not selling anything.

If your role has been eliminated as part of a layoff, the Department of Labor’s Rapid Response services can connect you with career counseling, job search support, training, and skills upgrading. These services exist because transitions like this are common. The system was built for them. You are allowed to use it. These services are not only for hourly workers. They are available to affected workers across many types of roles, including professionals and managers.

Outside the public system, the most useful conversations are usually with people one or two steps ahead of where you are: someone who recently made a similar move, a former colleague in a related field, a recruiter who works in the space you are looking at. They will tell you things a job board cannot.

A note on what is reasonable to ask for.

If your organization is making changes because of AI, it is fair to ask for specifics. Which tasks are being automated? Which roles are being redesigned? Which skills will matter more? What support is being offered to people whose work is changing?

If you are mid-career, that may also include internal redeployment options, outplacement support, severance timing, benefits continuation, and clarity on who owns the next-step communication.

Asking those questions is fair, and it is not disloyal. It is the kind of clarity that makes good planning possible. The organizations doing this well will have answers. The organizations doing it less well will not, and that itself is useful information.

One thing to do this week.

If you only do one thing after reading this, do this one. On a piece of paper or a blank document, write out the three or four things you do at work that depend most on judgment, relationships, context, or accountability. The work that would be hard to hand to anyone else, person or machine.

That list is your starting point. It is the thing you build the next move around. It is also a reminder, on the days you need one, of what you bring.

The work is changing. You can change with it.

At RightSeat, we work with leaders on the workforce question inside every AI strategy. But this piece is for the person living inside that question. RightSeat. Human co-pilots for your AI journey.