AI in hiring wasn’t even on most leaders’ radar in the summer of 2025. I was sitting across from a CTO, talking about AI adoption, hiring, and whether their organization needed to start screening candidates for AI attitude and actual usage. Their response was direct and, at the time, completely unbothered:
“Tim, I don’t think we have to worry about that. We’re in a bubble.”
Less than a year later – same organization, same leadership team – they are all in on AI. The executives are saying, unambiguously, that AI must be part of their hiring strategy for every hire. Not because the tools got shinier, but because they finally looked around and realized that every role in their organization is a knowledge-work role, and every knowledge-work role is about to be AI-touched.
That conversation has repeated itself, in various shapes, across many of the leaders I work with. The details change. The language changes. The industry changes. But the underlying shift is the same: what was “we have time” in mid-2025 is “this has to be table stakes now” in April 2026.
And it’s not just CTOs. I’m having this conversation with CEOs. I’m having it with VPs across functions that have nothing to do with engineering. I’m having it with operations leaders, finance leaders, marketing leaders. The shift is happening at the very top of the org chart, not somewhere down in the tooling layer.
This post is about that shift: what I was hearing a year ago, what I’m hearing now, and what I think it means for both sides of the interview table.
What I Was Hearing in Mid-2025
The “we’re in a bubble” line wasn’t unique to that one CTO. It was the most common shape of a response I heard throughout last year. When I’d raise questions like:
- “Are you screening candidates for AI attitude and actual usage?”
- “Are you funding a real plan for your teams to adopt AI?”
- “Are you setting a baseline of AI fluency you expect people to meet?”
The answers tended to land in one of a few familiar places.
“We have time.” AI is moving fast, but we’ll catch up whenever we decide to.
“Our market is different.” Our customers, our regulatory environment, our domain – those insulate us for now.
“Our people are fine.” Nobody on the team is asking for this, so it must not be urgent.
“It’s not really an interview topic.” We interview for skills and culture fit. AI can come later.
I wasn’t trying to be a doomsayer in those conversations. My point was always pretty practical: this is going to show up in how you hire and how competitive your teams can be, and you can get ahead of it or you can get caught by it. In most cases the suggestion landed politely, and then very little changed. Traditional interviews continued. AI stayed a side topic.
That was the norm less than a year ago.
What I’m Hearing Now
Here’s what’s different.
Many of those same leaders, in the same organizations, sometimes the exact same people who told me they were in a bubble, are now saying something almost unrecognizable compared to a year ago. Often without me bringing it up first.
“AI has to be part of every interview we run from here on out, every department. We at least need to understand where candidates stand and how they’re actually using it.”
“We shouldn’t be hiring people who are resistant to this, or who aren’t trying to learn it on their own right now.”
“We need everyone on the team moving in the same direction on AI, not figuring it out on their own.”
AI in hiring has gone from a side topic to the first lever many of these leaders are willing to actually pull. I want to be careful with this point, because attitude and execution are not the same thing. Plenty of organizations are still talking more than doing. Many are in the early, messy part of actually turning intent into adoption. But the attitude has shifted in a way I wasn’t seeing even six months ago, and once that attitude shifts at the top, the hiring process is usually the first thing to follow. It’s the cheapest, fastest lever a leader has. You don’t need a budget, a vendor contract, or a six-month program to change what questions you ask in an interview. You just have to decide it matters.
And right now, across a striking number of organizations, leaders are deciding it matters.
Why AI in Hiring Showed Up at the Top of the Interview First
I want to spend a moment on why AI in hiring is showing up in interviews first, because I think it’s easy to miss. The broader market signal has been there for a while – the kind of trend tracked in places like the Stanford AI Index – but the place it lands hardest in the day-to-day life of an organization is the interview loop.
The reason is not that leaders suddenly want to trivia-quiz candidates about prompt engineering. The reason is that the smart ones are starting to understand AI fluency is a team-level capability, not an individual preference. A team where half the people have strong AI intuitions and the other half are avoiding it isn’t a “mixed” team. It’s a team that can’t operate coherently, because every shared workflow, every handoff, every review gets pulled in two directions at once.
Once you see it that way, hiring becomes the place where that baseline either gets reinforced or eroded. Every new hire is a hire into a shared baseline of proficiency the team is trying to establish. If you hire someone who is actively resistant, or who genuinely has no working relationship with AI, you’ve just added friction to the thing leadership is trying to move. Do that a few times in a row and you’ve quietly guaranteed your team can’t keep up with the ones that didn’t.
That’s the logic the leaders I talk to are now arriving at. And it’s why the interview process – boring, unglamorous, often overlooked – is the first visible place the shift shows up.
(There’s a much bigger conversation about what it actually takes to build that shared baseline inside a team: shared workflows, common tools, sponsored time to learn, executive buy-in. That’s its own post, and I’ll write it. For now, the point is narrower: the team logic is what’s pushing the hiring bar up, and the hiring bar is what everyone on both sides of the table is about to collide with.)
The Part Individuals Need to Hear
If you are a knowledge worker reading this, here’s the message, directly:
You cannot cram your way to AI fluency in the two months before an interview.
This is the single biggest misunderstanding I see right now around AI in hiring. Some people are hearing the signal, looking at the calendar, and quietly thinking: if it gets urgent, I’ll take a couple of courses, watch some YouTube, and I’ll catch up.
That plan does not work.
AI fluency, the kind that holds up in a real interview and more importantly in a real job, is not a body of knowledge you memorize. It is a set of intuitions you build up through repetitions. Lots of repetitions. Daily use. Trying things, failing, noticing why they failed, trying them differently. Learning when the tool is great, when it’s dangerous, when to trust it, when to throw its output away. Building a gut-level sense of how these systems behave under real pressure. None of that comes from a course.
When a hiring manager says “walk me through how you’d use AI to approach this problem” – and that question is coming, in interviews across every knowledge-work discipline – the answer is going to come from your gut, not your notes. You either have the reps, or you don’t. And it will be obvious within about two sentences which one is true. No training course is going to prepare you for a question you weren’t prepared for. Only repetitions do that.
So if you haven’t started seriously, start now. Not next quarter.
- Pick a real task you do every week and rebuild it with AI in the loop. Not a toy problem. Something you actually own.
- Use AI every day, on real work. Every day. Even when it’s slower at first, because it will be slower at first.
- Pay attention to what worked and what didn’t. Keep a running personal log. This log becomes your intuition, and it also becomes your interview answer.
- Learn enough about how these models actually work to talk about them without hand-waving. Not ML-researcher level. Enough that context, tokens, hallucinations, and failure modes are things you understand, not just words you’ve heard.
- Accept that this is a long-arc skill. You are building intuition, and intuition only compounds with time. There is no shortcut.
The risk if you don’t start now isn’t that you miss out on the shiny new thing. It’s that by the time the interview market has fully caught up – which, based on what I’m hearing, is months, not years – you will be competing for knowledge-work roles against people who already have a year or two of daily practice behind them. That’s a hard gap to close from a standing start.
The Part Leaders Need to Hear
If you are a leader reading this, the message is different but related.
The shift you’re feeling is real, and the interview process is the right place to start, but only if you take it seriously.
Adding an AI question to the end of a traditional interview loop as a throwaway is not the same as taking AI in hiring seriously. Taking it seriously means:
- Knowing what answers you are actually looking for. “I’ve used ChatGPT once” is not the same as “Here’s a workflow I rebuilt around AI and here’s what I learned when it broke.”
- Being willing to not hire strong traditional candidates who are flatly disengaged from AI. That’s the hard part, and it’s where most hiring processes quietly flinch.
- Recognizing that the reason you’re screening for this is that your existing team needs reinforcement, not dilution. Every hire either raises the baseline or lowers it.
And, this is the part I can’t soften, this only works if you, personally, are bought in. Not “approve the budget and move on” bought in. The kind where your team sees you using it, talking about it, and making it clear that fluency with AI is an expectation, not an extracurricular. Leaders set the ceiling on this. I’ve written before about why AI initiatives quietly fail when leadership doesn’t commit, and the same pattern applies here. Nothing in the interview process fixes a leadership team that still secretly thinks AI is someone else’s problem.
Closing Thoughts
The reason I wanted to write this is not to revisit old conversations. It’s because something has genuinely changed in the last few months, and the people most affected by the change are often the last to hear that it’s happened.
The attitudes at the top have shifted. The leaders I work with feel it, and they’re acting on it, starting with the place they can move fastest, which is how they hire. The execution is going to vary. The intent is not.
For individuals: start now, use it every day, build the intuitions the slow way, because there is no fast way.
For leaders: take the interview seriously, because right now the interview is the fastest, highest-leverage change you can make, and everyone can tell the difference between leaders who mean it and leaders who are just adding a question.
Either way, the “we have time” story is the one thing I’d retire first. AI in hiring isn’t a future trend – it’s already the conversation happening at the very top of the org chart. The CTO who told me we were in a bubble is retiring that line right now, in their own organization, in real time. A lot of their peers are doing the same thing. If you’re still holding onto it, on either side of the interview table, you are holding onto something that has very quietly stopped being true.
