As AI interviewers and automated screening become standard, HR leaders argue the technology’s real value lies in what it frees humans to do—not what it replaces.
By Gillian Manning
AI has moved from experiment to expectation in recruiting. Most HR leaders—91%—now say AI has become essential to managing application volume, and 89% say it has helped them find better candidates, according to Paylocity’s 2026 State of Employee Recruitment report. Adoption is the heaviest in resume screening (67%), interview scheduling (59%), and job description writing (57%). But usage drops sharply for candidate engagement and interviews (35% each)—the moments where a wrong signal carries real consequences.
Applicants are noticing the difference. A May 2026 Greenhouse report found 63% of job seekers have now been interviewed by AI, up 13 points in six months. Yet 38% have walked away from a hiring process specifically because it included an AI interview, and another 12% say they would. The top reasons: pre-recorded interviews scored by AI with no human present, undisclosed AI use, and AI monitoring during the process.
For Julie Mann, CHRO and founder of Lead with Collective and co-founder of the AI-focused firm Compound, that gap between adoption and trust isn’t a technology problem, it’s a design problem.
Liz Andora, chief people officer at DHI Group, sees a similar tension from the employer side of the table. She says, “The applications where we have seen the most positive impact are those that help people get to the right information faster while keeping humans at the center of hiring decisions.”
Where AI Earns Its Keep
Mann says the biggest wins so far have come from what she calls “the unglamorous side of recruiting:” the administrative work that really consumes recruiters’ time without adding relationship value. AI-assisted job description drafting, automated scheduling, and early candidate communications, she says, have been “pretty transformative,” freeing recruiters to do the work only humans can do, like building relationships, reading the room, and advocating internally for candidates.
She has also seen AI support skills-based hiring, helping organizations move away from pedigree-based screening toward assessing demonstrated competency—a shift she says has opened up talent pools “that were previously invisible.”
AI adoption is the heaviest in resume screening (67%), interview scheduling (59%), and job description writing (57%).
Andora says there’s a more pointed use case on the hiring side: separating real applicants from fake ones. As application volume climbs, she says AI has become essential not just for identifying qualified candidates but for verifying that they’re genuine.
“In today’s world, we receive ‘fake’ candidates and AI can help us screen them out,” she says. When looking at the ROI on this effort, Andora says the calculation goes beyond hours saved. “We look beyond time saved to whether the technology is improving the quality of those connections and the experience on both sides,” she says.
The Line AI Can’t Cross
But Mann is unambiguous about where automation should not go. She says, “Any moment when a candidate forms a lasting impression of your organization must be human-led, full stop.”
That includes the final hiring decision. “That accountability that comes with choosing to invest in a person, and just the human dignity of being chosen for the role—that demands a human in the seat,” she says. AI can surface, rank, and inform, but “it definitely can’t own that decision because that’s a relationship moment.” Structured interviews probing values, motivation, or how someone has navigated adversity require, in her words, “a nuanced listener that no algorithm can reliably replicate.”
The offer conversation and onboarding, she adds, are moments of candidate vulnerability tied to a major life decision—and if a chatbot is the last touchpoint before someone signs, “it says something” about how the organization values that person, whether intended or not.
Andora draws a similar line. Hiring decisions, she says, still need to be made by humans, because understanding someone’s experience and how they might perform in a new role requires context that’s difficult to get from data alone.
“AI can help compile a comprehensive list of information about a candidate going into an interview,” she says, “but that’s where the conversation becomes important, because it gives both the employer and the candidate a better understanding of whether the opportunity is actually a good fit.”
For Andora, the ethical boundary comes down to explainability. “I believe we cross that line when we give AI the power to make consequential decisions about an applicant without being able to clearly understand or explain how that decision was reached,” she says, adding that not every signal AI can detect belongs in a hiring decision—it has to have a meaningful connection to someone’s ability to do the job.
Strategic Design, Not Blind Technology
Among Greenhouse’s surveyed candidates who walked away from opportunities, the top triggers were pre-recorded video interviews scored by AI with no human present (33%), undisclosed AI use (27%), and AI monitoring during the process (26%). Nearly 20% of surveyed candidates call for less AI in the hiring process.
Asked how organizations avoid the dystopian-feel that can drive candidates away, Mann reframes the question entirely: “It’s a design question, and not a technology question.”
Speed serves candidates when it means faster scheduling, faster status updates, and faster decisions—the absence of which, she notes, causes organizations to lose talent to slow processes every day. But speed becomes a liability when it compresses genuine human engagement.
“If efficiency means the candidate goes from application to offer without having a real conversation, you haven’t built a faster process,” she says. “You’ve built a hollow process.”
Andora says the next challenge is distinguishing technology that supports a recruiter from technology that replaces the interaction with a candidate altogether.
“The interview process has always held value, because there is context that comes through in a conversation that may not be apparent from a resume or an automated assessment,” she says.
Transparency with candidates, she adds, is non-negotiable. “Candidates should understand when AI is being used and how it is contributing to the process. Maintaining that transparency will become more important as these technologies become common in hiring,” she says.
Mann lists several other non-negotiables: informed consent and transparency about what data AI tools collect and who has access to it; regular bias auditing across gender, race, age, and disability status; and a human “always available” to override AI recommendations before a final decision is made.
At Compound, that accountability is mapped through what she calls a “hybrid accountability chart”—identifying the human orchestrator who owns the final outcome for any AI-assisted process.
And the numbers back up Mann’s non-negotiables. Candidates surveyed by Greenhouse call for upfront disclosure about AI use (44%), a clear explanation of what AI is measuring (39%), and the option to request a human interview instead (46%).
What the Future Holds
Looking ahead, Mann expects AI-powered scheduling, skills-based assessment platforms, and job description optimization to become standard practice. She’s more skeptical of tools claiming to read personality or emotional fit from facial and voice analysis. She says, “The science isn’t there.”
She expects fully automated, end-to-end AI interviewers to face pushback too, citing a Pew Research statistic that two-thirds of U.S. adults say they avoid applying for jobs where AI makes hiring decisions.
Her closing advice for HR leaders is to treat AI as infrastructure, not a solution. “Design before deploy,” she urges, calling for leaders to start with the talent strategy question first, then finding the tool that serves it, rather than starting with the tool.
Andora sees a parallel shift building on the candidate side. “Candidates now have access to many of the same capabilities employers are using, which changes how people prepare for interviews and communicate their experience,” she says.
Employers, she cautions, can’t assume the hiring practices that worked a few years ago will work exactly the same today. She says, “The organizations that adapt well to these changes will be the ones that continue to rethink their process as the technology and the behavior around it evolve.”
