By: Audrey Denise Cachuela
Laura Simms watches smart, capable professionals get better and better at running in the wrong direction. She founded Your Career Homecoming and coaches high achievers across tech, media, government, and the arts. They sharpen their résumés, polish their LinkedIn profiles, and use every tool available to move faster. They rarely stop to ask whether the destination is worth reaching.
An AI tool can rewrite a résumé, map a skill set, and prep someone for an interview in minutes. It cannot tell that person whether the job waiting on the other side of the interview is one they actually want.
Most of the conversation about AI and careers is about job loss. Simms points at a quieter risk. People are getting remarkably efficient at chasing careers they’ve already outgrown. Speeding up a job search says nothing about whether the job is right. That gap is the whole ballgame, and AI widens it.
AI Career Planning Excels at Optimization, Not Direction
Give a tool a clear goal, and it delivers. Ask it to tighten your résumé, and it flags the repetition and surfaces your strongest work. Ask it to prep you for an interview, and it generates questions tailored to the role. None of that requires the tool to know a single thing about you. It needs a direction you’ve already chosen, and it works fast inside that direction.
Using these tools well is a real skill, and refusing them makes little sense. The mistake happens somewhere else, when speed starts to feel like direction, and getting faster at the job convinces someone they’re getting closer to the right one.
Those are two different questions. Optimization asks how to improve a position. Fulfillment asks whether the position deserves improving in the first place. One shows up on a performance review. The other is whether the work still means anything and whether it fits the life you actually want. Progress on the first can end up costing you the second: a promotion that boxes you in, a raise that takes your schedule, a decade of strong reviews in work that stopped being yours years ago. None of it shows up until the gap is too wide to ignore.
And it’s widespread. Global employee engagement fell to 20% in 2025, its lowest since 2020 (Gallup, 2026). Plenty of people are showing up, performing, hitting every mark, and feeling nothing about the work itself.
The Trap is Getting Better at the Wrong Career
That gap turns dangerous the second you point AI at a path you’ve never actually examined. Efficiency feels like progress because it produces things you can point to: more applications out, a sharper headline, projects done early. None of it confirms you want the future you’re building.
Simms sees the same pattern constantly, and it has a specific cause. Success generates its own evidence that you should keep going. Employers reward competence. Colleagues lean on you. Family calls the job stable, impressive. Every win makes leaving harder to explain, so the cost of staying gets buried under the cost of going.
Here’s the line her clients don’t want to hear. Competence does not prove fit. You can be excellent at a job you checked out of years ago, and that excellence becomes part of the trap. It keeps generating praise long after you stopped caring about the work.
Feed an AI tool your titles, your skills, your salary target, and it optimizes a more polished version of the path you’re already on. That’s what the input asked for. It has no way of flagging that continuity might be the actual problem. This is why career change is hard even for resourceful people. Most tools start with what you’ve done and ask what’s next. A decision that changes your life has to start somewhere else, with what you want the work to accomplish, what you need from it, what kind of life you want while doing it. Start from the wrong end, and you end up more efficiently stuck than before.
Simms knows the weight of this because she carried it. Leaving acting wasn’t swapping one job for another. Acting had shaped her identity, her community, her income, how she saw herself. Her transition started the day she stopped asking what she should do next and started asking why she wanted to work at all. A tool can help you think through a question like that. But it cannot answer it for you.
That’s the category no algorithm touches. AI can correctly note that consulting experience transfers to operations. It cannot register the grief of walking away from an identity you spent fifteen years building. It cannot weigh how much travel your family can absorb, or tell whether leadership actually energizes you or just confirms that other people find you capable. It can analyze what you say your values are. Only you can judge whether your choices reflect them, and the two diverge more often than anyone admits.
In a Shifting Market, Knowing What You Contribute Beats Guessing What Survives
None of this means standing still. AI is genuinely changing white-collar work. The OECD finds it’s good at automating the kind of complex thinking educated professionals get paid for, which puts a lot of those roles in real flux, even though there’s no sign yet that AI is shrinking overall employment (OECD, 2026). The part people miss is that a task getting automated is a long way from a job getting erased. Confuse the two, and you decide from panic instead of clarity.
Knowing what you bring to the market matters more than predicting where it’s headed. Nobody can reliably guess which job title survives the decade. What you can know is what you’re good at, the conditions that let you do it well, and where that meets a real need. Take two marketing directors. One defines herself by the title, so when the role shifts under her, she’s stuck. The other knows she reads audiences well, shapes sharp positioning, and connects business goals to what customers actually need. She lands on her feet whatever her next title turns out to be. Titles change. Capabilities travel.
Do the Work First, Then Hand AI the Wheel
Most people do this backwards. They start a career change by updating a résumé, scrolling boards, messaging a recruiter. It feels productive because something is moving. Movement without direction is just noise, and anxious people mistake noise for progress every time.
Before asking AI what roles fit your résumé, sit with a harder question. What does the next chapter need to provide? Which parts of the current work still create energy, and which demands have become unsustainable? Be honest about the life attached to each option too: the pace, the autonomy, the income, the toll on the people you love. And interrogate why a direction appeals. A role can fit you, or it can just be prestigious, familiar, and easy to explain at a dinner party. Most people can’t tell those two apart without sitting still long enough to actually look.
That’s the one part of the process no tool can do for you. Everything after it, the research, the comparisons, the search itself, is where AI earns its place. It weighs paths against your criteria, pokes holes in your assumptions, drafts questions for an informational interview, spots patterns across roles instead of handing you a verdict. Lead with clarity about what you want and the same tool becomes a way to investigate options that reflect your real priorities. Open the chatbot the moment restlessness shows up at work, and you’ll get a polished version of the path you were already on.
So before you let AI touch your résumé again, stop and ask whether that résumé still points somewhere you want to go. Simms built Your Career Homecoming for that pause, a place to get honest about the work and the life you’re actually choosing, before you hand the technology the wheel.
