Can you do the job, and are you even real? 🤔

Exaggerated resumes and fake candidates have always existed in hiring, but AI has amplified the problem.

Recruiters are no longer just asking, “Can this person do the job?” They’re also having to ask, “Is this person even real?”

Fake candidates and bad actors aren’t just international scammers applying to U.S. jobs. They’re also real candidates in the U.S. using AI to appear as though they have skills and experience they don’t actually possess.

Many of the verification methods recruiters used to rely on are becoming less effective as AI continues to evolve.

With AI becoming more accessible, bad actors can now generate dozens or even hundreds of resumes tailored to specific job descriptions in minutes, inventing projects, responsibilities, and accomplishments.

Those fabricated experiences can then show up in AI-generated portfolios. AI can create websites, GitHub repositories, design portfolios, presentations, and writing samples that make someone appear way more experienced than they actually are.

Candidates can also use hidden AI tools during video interviews that listen to questions and generate answers in real time. More concerning, AI can be used to create deepfakes and altered appearances using voice-cloning and face-altering technology.

Someone could even combine a real LinkedIn profile, fake work history, AI-generated photos, and fabricated references to create an entirely fictional candidate. If all of that wasn’t enough, AI can also generate fake reference letters, company websites, email addresses, and other materials used to verify experience that never actually existed.

Yikes.

Not only does this elongate the hiring process, but it likely takes away opportunities from genuine job seekers, and can make remote work harder to justify.

How are companies combating this?

No solution is guaranteed to work 100% of the time, whether a candidate is real but lied about their experience or a candidate is completely fake. Companies know that, but they’re implementing processes to at least minimize the risk.

Some companies are bringing candidates on-site for at least one round of interviews, especially the round where they need to prove their skills. Others are asking candidates to present a government ID at some point in the process, even though they know IDs can be falsified.

Many companies now require candidates to keep their cameras on so interviewers can look for signs that someone, or something else, is feeding them answers off-screen. Some candidates may even be asked to wave their hand in front of their face or perform a simple action to help detect deepfakes or manipulated video.

Interviewers are also asking more specific questions and expecting more detailed answers. Anyone can give high-level responses, so the more specific a candidate is about their experience, the harder it is to believe they made it up. Companies are also including more exercises that resemble the actual job instead of asking questions that can easily be answered with AI running on another screen.

This part isn’t new, but recruiters are spending more time cross-referencing resumes against GitHub, LinkedIn, personal websites, publications, and previous employers. Many are also moving reference checks to be earlier in the process so they don’t spend weeks interviewing someone they can’t actually hire.

Companies are also investing in platforms and technology that verify experience or attempt to detect deepfakes, voice changers, and pre-recorded video.

AI is forcing companies to rethink how they evaluate talent, but it’s also forcing them to rethink trust. The question used to be, ‘Can this person do the job?’ Now it’s, ‘Can we verify that this person is who they say they are?’ The challenge will be figuring out how to raise trust in hiring without making the process even more painful for companies and candidates alike.