Every week I hear the same questions from job seekers:
Am I being screened out by AI before a human ever sees my resume. How do I beat the AI in recruiting. Is my application even making it to a recruiter.
People keep asking the same questions about AI in recruiting so often and I think there’s a big gap between what’s actually happening and what people think is happening.
So I pulled two TA leaders from my Promptmates community, including Logan and Leandro, and asked them the same set of questions about how AI is actually being used in recruiting today.
What came back was not a single narrative.
First, what both leaders agree on
There is no version of recruiting today where AI is fully running the process end to end.
AI is not autonomously sourcing, screening, ranking, and hiring candidates without human involvement.
Where AI is showing up is in support roles inside the workflow. It is being used to reduce manual effort, speed up parts of the process, and improve access to information.
That point was consistent across both responses.
Where their perspectives start to split
The biggest difference is how mature they believe AI adoption actually is across the market.
One leader, Leandro, sees AI as still early and unevenly adopted. In his view, most companies are not using AI in the way candidates assume. Part of that comes down to adoption itself. As Leandro put it:
“Having the tools is one thing. Going through the change management and digital transformation to embrace those tools and change the behavior of people doing the job for many years is something completely different.”
He estimates AI-powered sourcing is still only being used by a small portion of the market, which might account for 1 reason why candidate experiences vary so dramatically from one company to another.
The other leader, Logan, sees AI as already embedded in many recruiting workflows. Not fully mature everywhere, but actively in use today and expanding quickly across sourcing, screening support, and recruiting operations.
Same topic. Different views on where the market is right now, but both see the same direction of travel.
Where AI is actually being used today
Across both responses, the practical use cases overlap more than the framing does.
AI is showing up in areas like:
- Sourcing support and pipeline building
- Market research and role intelligence
- Intake meeting transcription and summarization
- Interview planning and preparation
- Internal workflow automation and tooling experiments
One view focuses more on structured system design and workflow architecture. The other focuses more on experimentation across different tools and stages of hiring.
But in both cases, AI is positioned as support infrastructure. Not decision maker.
Recruiters are still driving the process.
What candidates are getting wrong
Both leaders strongly align here.
Candidates are overestimating how much AI is actually doing in hiring decisions.
There is a common assumption that AI is filtering candidates heavily before a recruiter ever sees them. Both responses push back on that idea.
The reality they describe is simpler.
Recruiters are still reviewing, deciding, and progressing candidates. AI is assisting with speed and efficiency, not replacing evaluation.
A second misunderstanding is assuming adoption is uniform across companies. It is not. Some teams are experimenting heavily. Others are barely using it. Most are somewhere in between.
That unevenness is part of what is creating confusion.
Where the advice for candidates splits
This is the most interesting divergence.
One perspective says candidates should stop worrying about “beating AI” and focus on fundamentals. Clear communication. Strong storytelling. Ability to translate experience into outcomes that make sense to a human reviewer.
The other perspective says the same but pushes harder on adaptation, saying candidates should be able to explain how they use AI in their work, how they think about tooling, and how they would operate differently in an AI-enabled environment. As Logan said:
“It’s really not an option in interviews these days to say I don’t like AI or I don’t plan to use it.”
His point wasn’t that every role requires deep AI expertise. It was that candidates should be prepared to explain how AI fits into their workflow, decision making, and day-to-day execution.
One is focused on clarity and communication and the other is focused on demonstrating AI fluency as a baseline expectation. Both are responses to the same shift and sit at different points on the adoption curve.
What I think is actually happening
The most accurate takeaway is not that one perspective is right and the other is wrong.
It is that AI in recruiting is uneven.
Some teams are early and experimental. Some are already integrating it into sourcing and workflow design. Most are somewhere in the middle.
That uneven adoption is exactly why candidates are confused. Their experience depends heavily on who they are talking to.
Which is why both of these things can feel true at the same time:
- “AI is not widely used”
- “AI is already changing recruiting workflows”
Both are real. They are just coming from different environments.
Acknowledgement
Shoutout to the members at Promptmates for providing their perspectives!