Hiring teams – it’s time to check IDs at the door

AI and hiring were supposed to make a great pair. Faster screening. Smoother workflows. Better signals in crowded pipelines. In many ways, they have succeeded.

But lately, they’ve started showing up with an unexpected plus-one: fraud. As automation takes on more of the early screening work, it’s also increasing the risk that misrepresentation, impersonation and bad actors slip through unnoticed.

According to our newly released 2026 AI in Hiring Report, 91% of recruiters and hiring managers say they’ve spotted or suspected candidate deception in the past year. The report goes beyond headlines to unpack how candidates, recruiters and hiring managers are actually using AI – where trust is breaking down, where risk is rising and where leading teams are adapting successfully.

This edition of Modern Recruiter focuses on that growing risk gap and how to best mitigate it.

How are the pros adapting? They’re doing the hiring equivalent of checking IDs at the door: Building in smarter checkpoints and pressure testing AI signals – not to slow things down, but to make sure the right people are getting in.

The Recruiter’s Desk: Four ways to manage risk in AI-powered hiring

According to our new AI in hiring report, 28% of recruiters encounter fraud multiple times per month, and 74% are more concerned about fake credentials than last year. As AI accelerates screening, managing fraud and security risk has become a core responsibility for talent teams. For this edition of The Recruiter’s Desk, we consulted experts Ariana Moon (Greenhouse), Hung Lee (Recruiting Brainfood) and Becky McCullough (HubSpot) for practical guidance on managing risk:

Tip 1: Treat AI as input, not authority. Ariana advises viewing AI “as an opinion from a smart coworker rather than a universal truth,” grounding decisions in clear competencies and human judgment.

Tip 2: Replace black boxes with glass boxes.“We need to evolve beyond the black box experience,” Ariana added, “and embrace a glass box mindset where teams can defend how AI is used.”

Tip 3: Build coordinated, end-to-end verification. Becky notes that “effective fraud management requires cross-business collaboration” so verification spans “from application to onboarding” and feels fair and consistent.

Tip 4: Demand explainability and oversight. Hung emphasizes bias audits, transparent reasoning and clear audit trails to keep AI-assisted decisions accurate and defensible.

Together, these practices help teams move fast while protecting trust, security and candidate quality.

Thank you

Thank you for reading this edition of Modern Recruiter! We’ll see you next time for more must-reads, events and open jobs to keep you updated on the latest news and insights in the industry.

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