AI Is Already the Generalist. Curiosity Is Your Edge

By Burt Brooks, Founder & CEO, PathAble

A few years ago I sat in a planning meeting with a job coach, a behavior therapist, and a program funder, and all three described the same client using three completely different vocabularies. The coach talked about natural supports and fading. The therapist talked about antecedents and reinforcement schedules. The funder just wanted to know the billable units. Nobody was wrong. They were speaking from inside their own department, and none of them had spent enough time in the other person's chair to translate.

That meeting is the whole argument, in miniature, for why "become a generalist" is bad advice for the AI workplace.

The Generalist AI Already Won

Here is the part nobody says out loud: AI is already a generalist, and a better one than most of us will ever be. It can write passable code, draft a passable memo, and summarize a passable report, all in a fraction of the time it takes a person to do any one of those things passably. If "generalist" means knowing a little about a lot, AI got there first, and it is not slowing down.

So when people say generalists will thrive after AI, they are not really talking about breadth of knowledge. They are talking about something AI still cannot fake: the soft skills that come from actually working alongside other human beings, in different roles, long enough to understand how they think. That is not the same thing as being a generalist. It is being curious about people who are not you.

Curiosity Is Not the Same as Being a Generalist

Do not set out to know a little about everything. Set out to understand how the people around you actually work. Sit in on the intake meeting even when intake is not your job. Ask the billing coordinator what makes her week harder. Ask the direct support professional what breaks down when a schedule changes at the last minute. You do not need to be able to do their job. You need to know their pain points, their language, and their workflow well enough that you could explain it to a stranger.

That is empathy built through experience and exchange, not something you can download. It is also, not coincidentally, the same thing I have argued makes a tool worth adopting: a DSP who was in the room when a system was designed trusts it more than one who was handed it cold, which is a pattern I wrote about in why direct support staff are not using the tech that could help them. The same curiosity that builds soft skills is what should be driving how we build tools in the first place.

AI Is Becoming the Glue Between Departments

This matters more, not less, as AI takes on more of the department specific data. AI is becoming the glue between departments, the thing that can pull a case note, a budget line, and a compliance deadline into one view. But glue holds pieces together. It does not decide what the pieces should be, and it does not notice when a solution that looks efficient on paper will fail the moment it meets an actual person. That is still a human job, and it goes to whoever bothered to understand the humans on the other side of every handoff.

Specialists Are Not Doomed, But They Do Have to Show Up

Specialists are not getting left behind. A great behavior therapist who never learns to talk to funders in their language is not doomed, but they will have a harder time adapting when the org chart shifts or the funding model changes. The people who adapt easiest are the ones who already built relationships across the departments AI is now stitching together.

AI handles the paperwork. It does not handle the person across the table. As it takes over more of the digital grind, it frees up the thing that was always the actual job, which is working well with other people. Go find someone outside your department this week and ask them a real question about how their job actually goes. That is the whole strategy.

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