AI in hiring: What private equity talent leaders are getting right

Highlights:

• AI’s biggest impact in hiring is freeing up humans, not replacing them. The most effective talent teams are using AI to automate prep work so they can spend more time on evaluation and relationships.
• Structured hiring is your defence against AI-polished candidates. Well-defined scorecards, case studies and back-channel referencing are what separate signal from noise.
• Trust is the central challenge. Rebuilding it requires transparency, clear data governance and human accountability at every step – paired with disciplined processes, not just faster tools.

Ask any operating partner in private equity (PE) or growth equity what makes or breaks a portfolio company, and talent comes up fast. The right CEO, the right go-to-market leader, the right operators closest to the product and the customer – these decisions shape whether a company scales or stalls.

But as the new Greenhouse benchmarking report, The Hire Standard, shows, the landscape for those decisions has shifted dramatically. Application volume per recruiter is up 412% while recruiter headcount is down 56%. Meanwhile, candidates are using AI to optimise CVs and prep for interviews, fraud and misrepresentation are rising, and the tools available to talent teams are evolving faster than most organisations can keep up.

At the PEI Operating Partners Human Capital Forum in New York City, Greenhouse brought together a panel of operating partners and talent leaders from across the private and growth equity ecosystem to get into the specifics: What’s actually working with AI in hiring? What’s not? And where should firms and portfolio companies be focusing right now?

The conversation was honest, practical and full of insights that extend well beyond the PE world. Whether you’re an operating partner advising a portfolio or an in-house recruiting leader trying to figure out your AI stance, here are the themes worth paying attention to – and questions worth bringing back to your team.

AI is automating everything except the parts that only humans can do

The panelists were clear: the biggest wins with AI in hiring come from eliminating the manual, repetitive work that keeps talent leaders from doing what only they can do.

Across the panel, we heard about workflows that auto-generate candidate briefings before every interview, scorecards that populate from call transcripts in seconds and tools that map back-channel reference networks from a LinkedIn profile in 20 seconds flat. One panelist described a daily briefing that hits their inbox at 5am – pulling together the candidate’s CV, the position scorecard and tailored interview questions – so they walk into every conversation fully prepared without scrambling between calls.

The point was less about AI doing the evaluating, and more so about AI doing the prep work so humans can focus entirely on evaluation, relationships and decision-making.

Bring this back to your team: Where are your recruiters and hiring managers spending the most time on tasks that don’t require human judgement? What would it look like to automate those – not to cut headcount, but to redirect that time toward higher-quality evaluation and candidate engagement?
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Structured processes and references matter more than ever

As candidates increasingly use AI to tailor CVs and polish interview answers, panelists emphasised that rigor is the real antidote to technology.

The firms seeing the best results are doubling down on structured hiring practices: well-scoped roles, clearly defined scorecards, case studies built into the evaluation process and, critically, robust back-channel referencing. Multiple panelists noted that when a candidate’s CV looks almost identical to the job description, you have to be smarter in your interview process to separate what’s real from what’s AI-generated.

This doesn’t mean rejecting AI – but it does mean making sure your process is strong enough that AI enhances it rather than obscures signals. If your interview process is tight, you’ll catch the gaps regardless of how polished the application looks.

AI shouldn’t replace the high-conviction calls that confirm great hires. When used right, it protects valuable time and brings reliable signal and trust into the hiring process.

^{– Meredith Johnson, Chief Product Officer at Greenhouse}

Bring this back to your team: How confident are you that your interview process would surface the difference between a candidate who used AI to match the job description and one who genuinely has the experience? What would it take to add one more layer of verification – a case study, a working session or a structured back-channel process – to your most critical hires?
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AI literacy is becoming a signal for leadership quality

One of the more forward-looking themes from the panel was the idea that a company’s use of AI – not just in hiring, but across all functions – is becoming a lens through which firms evaluate leadership.

While panellists agreed this isn’t yet a deal-breaker in investment decisions, the direction is clear. How a CEO or management team embraces AI tells you something about how modern, adaptable and competitive they are. Firms are increasingly looking at AI adoption as part of the broader picture of operational excellence and readiness to scale.

Several panellists noted they’re now surveying portfolio company people leaders on what they’re doing with AI across all talent functions – not just to evaluate, but to create opportunities for portfolio companies to learn from each other.

Bring this back to your team: If a board member or investor asked your leadership team to describe your AI strategy for hiring and talent, what would the answer be? Is there a clear, intentional approach – or is it ad hoc? What would a 90-day plan to develop a position on AI in hiring look like for your organisation?
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The “new CEO onboarding” question is a litmus test

When the panel was asked what they’d advise a new portfolio company CEO on AI and hiring, the answers converged on a few themes:

• Use AI for deep thinking, not just speed. Don’t chase tools for the sake of having an AI strategy. Be clear about what you’re trying to accomplish, then evaluate whether AI accelerates that.
• Build “what can I automate?” into the first 90 days. Make it part of the onboarding process for any new leader. The firms seeing the most impact are the ones where this question keeps getting asked – not just once, but continuously.
• Rethink headcount as a measure of scale. One panellist suggested that the traditional view – bigger team equals better execution – is giving way to a model where you have two workforces: your people and your agents. Understanding what each is doing and measuring their impact is a new leadership competency.
• Don’t let AI replace rigor. Speed is great, but decisions made fast without structure don’t hold up. Encourage leaders to pair AI tools with disciplined processes.

Bring this back to your team: If you were onboarding a new leader next Monday, what would you tell them about AI and hiring? What would you steer them away from? Use that answer as a starting point for codifying your firm’s or company’s stance.

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Trust is the through line

Underneath every topic – tools, fraud, onboarding, evaluation – there was a consistent theme: trust is in crisis, and rebuilding it is everyone’s job.

Candidates don’t trust hiring processes. Recruiters don’t trust that applications are real. Hiring managers don’t trust that AI-polished candidates can actually do the work. And firms are still building trust in AI tools themselves.

The panellists navigating this best are doing so with transparency, structure and a commitment to keeping humans at the centre of every hiring decision. That extends to compliance, too. An audience member asked what many were thinking: How are you actually getting these AI tools approved internally? Where does the data go? The honest answer: it’s a long, ongoing conversation – one that requires partnership between talent, legal and IT, with clear guardrails around what data goes into which tools and how it’s governed. The flashiest AI capabilities don’t matter if the platform can’t pass your security review. Clean data, reliable outputs and defensible compliance should be table stakes.

Bring this back to your team: Where is trust breaking down in your hiring process? And do you have a clear process for evaluating AI tools – including where candidate data is stored, who has access and how it’s governed?
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What comes next

The conversation at PEI made one thing clear: the firms and companies that treat talent as a strategic function – not an administrative one – are the ones that will win in this environment. 

Whether you’re an operating partner looking to create a hiring advantage across your portfolio or a talent leader trying to modernise your process, the key is to start with intentionality: know what problem you’re solving, build structure around it and then layer in AI to make your team faster and your decisions stronger.
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Looking for more insights? 

For PE and growth equity firms: If you’re interested in learning how Greenhouse partners with firms to make hiring a portfolio-wide value-creation lever – including preferred pricing, operator programming and thought leadership – tell us about your firm here.

For talent and recruiting leaders: If you want to see how the Greenhouse hiring platform equipped with intentional AI can help your team cut through noise, hire faster and make confident decisions, request a demo.

FAQs

How is AI being used in hiring today?
The most effective applications right now focus on preparation and coordination – auto-generating interview briefings, populating scorecards from transcripts and mapping reference networks. AI handles the repetitive work so recruiters and hiring managers can focus on evaluation, relationships and decisions.

How can hiring teams verify candidates who use AI on their applications?
Structured hiring practices are essential. That means clearly defined scorecards, case studies or working sessions built into the process and robust back-channel referencing. The goal is to create enough touchpoints to distinguish genuine experience from a well-crafted application.

What should companies look for when evaluating AI hiring tools?
Start with governance. Where is candidate data stored? Who has access? How are AI outputs audited? Look for tools that embed AI within structured workflows – where every output is transparent, every decision has a human owner and compliance is built in from the start.
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Curious for more information on how to best navigate hiring in this new AI landscape? Download the 2026 AI in Hiring Report.