Pull up a job posting in your field from 2023. Now open one posted this week for the same role. Read them side by side.
The title is probably the same. The salary band might even look familiar. But somewhere in the middle, something shifted. The tasks that used to be the whole job are now a single line that says "using AI tools." What is left is a different thing entirely.
This is the conversation I think matters more right now than which model beats which benchmark. Not whether AI is taking jobs, but how quietly it's rewriting the ones that stay.
The IBM example
IBM did something interesting this year. Instead of cutting entry-level roles the way everyone assumed they would, they tripled hiring for them. But they rewrote every single job description first. Junior developers now spend less time writing code and more time with customers. HR hires do not do manual intake anymore, they supervise the AI that does. Same title. Same paygrade. Completely different day.
Their CHRO was direct about it: the entry-level jobs from two or three years ago, AI can do most of them now. So they did not eliminate the roles, they changed what the roles are actually for.
The language shift nobody talks about
Go look at what Atlassian, Shopify, and Stripe have been publishing in the last six months. The language in job postings has shifted in a way that is easy to miss if you are not looking for it. Words like "execute," "manage," and "develop" are getting replaced by "oversee," "translate," and "evaluate." The job is less about doing the thing and more about deciding whether the thing was done right.
For people mid-career, that is actually good news. The parts of the job that were repetitive and frankly soul-destroying are going away. What is left is the stuff that required human judgment anyway: the edge case conversation, the moment where the output looks fine but something is off and you have to articulate why.
The harder news
If your resume still describes the 2022 version of your job, you are speaking a language that companies are quietly retiring. Not because your experience does not matter, but because the words you are using to describe it now map to tasks that get routed to a model before a person sees them.
The interview changed too. Companies that used to mark you down for using AI during a technical session are now watching how you use it. They are not checking whether you can solve the problem. They are checking whether you catch the mistake the model makes, whether you know enough to push back, whether you treat the output as a starting point or a final answer.
One practical thing worth doing this week: search your own job title on LinkedIn and read five recent postings properly. Not to apply, just to see what language is showing up that was not there before.
The job description did not lie to you on purpose. It just got rewritten while you were busy doing the job.