The recruiter’s edge in AI-driven hiring: Human judgment
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Key highlights:
- The recruiters winning in an AI-heavy funnel are the ones using AI to handle volume and reserving human judgment for the decisions that matter: reading the person, defining the target and making the call.
- The old signals no longer work: a polished resume no longer proves a strong candidate, so reading the person behind it is now the core recruiting skill.
- Define good before you screen: most bad hires trace back to a fuzzy target, and a sharp intake scorecard prevents them.
- Slow down to go fast: a confident hire is reachable at around four interviews, so knowing the threshold beats stacking rounds that don’t move the decision.
Ask almost any recruiter how the job feels right now and you’ll hear a version of the same thing: more reqs, more applicants, more tools, less time. The applications keep pouring in. The tech stack keeps growing. The pressure to move faster never lets up. Something has to give, and usually it’s the one thing that made a recruiter good in the first place – judgment.
The busywork is real: 34% of recruiters spend up to half their week filtering spam and junk applications. So it’s no surprise AI is a welcome relief – more than happy to take the sorting, drafting, scheduling and summarizing off your plate. The trouble starts once it’s humming along and it gets awfully tempting to let it start doing the thinking too.
Across Season 2 of the Recruiting Roadshow, five recruiters kept landing on the same point: let the machines carry the load, but keep the judgment human. You’ll hear from all of them here – Julianne Streff, Principal Recruiter at BWBacon Group; Katie Wagner, Founding Partner at Talent By Design; Beth Marceau, recruiter and former head of talent; Laurie David, VP of Talent Acquisition at The Fedcap Group; and Andrew Delabar, a RecOps leader at Hudson River Trading. Andrew said it most bluntly: there are teams out there using AI to make bad decisions faster.
There are teams out there using AI to make bad decisions faster.
– Andrew Delabar, RecOps leader at Hudson River Trading
So here’s the idea worth pinning to the wall. Let AI carry the volume. A recruiter’s edge is what they do with the hours it hands back, and the ones pulling ahead are spending every one of them on the human work that decides who actually gets hired. Here’s where that time goes.
Re-anchor your signal
Start with a tougher question than “Is this a strong resume?” Try “Who is this, really?”
For years, a clean, well-built resume was a fine stand-in for a strong candidate. With 74% of candidates now using AI in their job search, anyone can polish, format and tailor a resume in seconds, and the document tells you less and less about the person behind it. Some of that crosses a line: 41% admit to slipping prompt injections into their applications, hidden instructions meant to game an automated screen.
Beth has watched the old logic flip on its head. “How the resume is set up is usually a good indication of potential fraud or lack of experience,” she says. The more flawless and keyword-perfect it looks, the more it might be worth a second glance.
So the skill that matters now is reading the person behind the paper. What are they actually motivated by? Where does their path solve the problem you’re hiring for, even when the titles don’t line up? What are the bullet points quietly leaving out? That read is pure judgment, and as Julianne put it, you can automate the whole workflow and standardize every scorecard and still miss completely if nobody has the capacity to treat candidates like people.
Define good before you screen
Of course, reading the person only helps if you know what you’re reading for. And most bad hires trace back to a target that was blurry from the start. If the team can’t say what good looks like before the search kicks off, no amount of screening rigor later will rescue the outcome.
That work happens at intake, and it’s judgment through and through. “A lot of companies today are still having trouble with what good looks like,” says Laurie. And it shows downstream: 45% of hiring managers cite difficulty telling qualified candidates from unqualified ones as a top challenge. Katie goes a step further: half the time the hiring manager can’t even name the problem they’re hiring for until a recruiter helps them find the words. Getting them there is the job.
So treat intake like the strategic conversation it is. Pin down the business case – what changes if this role is filled well, what stalls if it sits open. Push past the job description to the outcomes. Ask what a great hire will have actually done 90 days in. Then turn those answers into a scorecard everyone signs off on before a single application gets opened. When the answers come back vague, dragging the manager toward specifics is your first deliverable, and the sharp target you build there makes every call that follows easier.
Verify the human, then let AI surface the rest
Once the target’s sharp, there’s a more basic question waiting: is the person in front of you actually who they say they are? Candidate fraud has gone from rare edge case to a Tuesday: 91% of recruiters have spotted or suspected candidate deception in the past year. Some of it is brazen – 31% have watched a different person show up to interview than the one who applied, and 18% have run into deepfake video interviews. Identity is something you now have to establish rather than assume.
From there, hand AI the thing it’s genuinely great at: a first pass. It’ll flag a candidate as a strong match for these reasons and a shakier one for those, and it’ll sort patterns across a mountain of applications in the time it takes to grab a coffee. What it can’t do is catch the nuance – the career gap with a story behind it, the odd-looking path that turns out to be exactly right. Julianne draws the line cleanly: “I like it for reviewing applications, but only after the humans-in-the-loop part of the process, not as a replacement of that.” AI narrows the field. A person makes the read.
Slow down to go fast
Here’s the counterintuitive part: the fastest way through is often to slow down.
When the desk is buried, every instinct screams push more people through, faster. But volume isn’t progress. One line from Laurie stuck with the whole season.
You’ve got to slow down in order to go fast. Speed can kill.
– Laurie David, VP Talent Acquisition, The Fedcap Group
Three strong candidates who fit the brief will beat thirty rushed screens that don’t, every time. And slowing down means knowing when to stop. Andrew points to research that says you can reach a confident hire at around four interviews, with every round after that piling on cost and calendar drag while barely moving the needle. Set the threshold, hold the line, and all those extra rounds stop eating your week. Deliberate hiring is what keeps you from running the whole search over again a quarter from now.
Spend the time on people
Every hour you claw back from admin is an hour you can put where it counts: the parts of hiring people actually remember. That’s the whole trade.
Spend it where only a human helps – coaching a hiring manager through a tough call, keeping a candidate warm and in the loop, giving feedback that lands like it came from a person. For Julianne, that last one is everything. “My goal is always that they still feel like they were seen, heard and valued,” she says, even when the answer is no. That’s employer brand in action, and it’s often the line between a candidate who happily comes back around and one who quietly steers their friends elsewhere.
Structure makes room for all of it instead of crowding it out. The more consistent your process, the more equitable your hiring – and the more room your team has to be human inside it, because nobody’s rebuilding the steps from scratch on every req.
The recruiter’s edge
The edge in this era is easy to say and hard to earn: pick the right tools, let them carry the volume and pour the time they hand back into judgment – defining good, reading the person, making the call. AI is very good at doing things faster. Deciding who belongs on the team? That part’s still yours.
The right AI gives recruiters time back for judgment. This AI evaluation guide walks through what to look for – and what to avoid – when adding AI to your hiring process.
FAQs
Can AI replace recruiters?
No. AI is well suited to high-volume, repeatable work like sorting applications, drafting and scheduling, and it can surface signal a recruiter then evaluates. The consequential decisions – who to advance, how to read a nuanced background, whether someone fits the team – stay with people. The recruiters getting ahead use AI to reclaim time and reinvest it in that judgment.
How is AI changing what recruiters should look for in a resume?
AI has changed how resumes get written. With 74% of candidates now using AI in their job search and 41% admitting to hiding prompt injections in their applications, a polished document is a weaker signal of quality than it used to be. A flawless, keyword-perfect resume can even point to possible fraud or thin experience. Recruiters should weigh the underlying substance – motivations, the story behind a path, evidence tied to the outcome being hired for – over formatting and keywords.
Which hiring decisions should stay with humans when using AI?
Any consequential judgment. That includes interpreting nuance in a background, reading a candidate in a live conversation, deciding who advances and delivering feedback. A useful rule is to bring AI into application review only after a human-in-the-loop step, so AI narrows the field and a person makes the read.
How can recruiters spot candidate fraud in a high-volume, AI-heavy funnel?
Candidate deception is now common: 91% of recruiters have spotted or suspected it in the past year, and 18% have encountered deepfake video interviews. The response is to establish identity rather than assume it. Add application questions that are hard to fake and quick to verify, and use live video screens to confirm the person and their skills, watching for AI-assisted or scripted answers. Treating verification as a standard step across stages catches problems before they reach a hiring manager.
Does using AI in hiring actually speed things up?
It can reduce administrative load, but speed is not the point. Moving candidates through faster without judgment tends to produce worse hires. The stronger use of AI is to free up time for the human work – defining the target, reading the person, verifying who’s genuine – so decisions are right the first time and don’t have to be redone.
