The best way to spot AI deception in interviews. 

AI is transforming the hiring process, reshaping how candidates search for jobs and how companies evaluate talent. For hiring teams, it accelerates early tasks like sorting and matching candidates, helping surface top technical talent from large pools. But for dishonest candidates, AI can be a tool for exaggeration—67% of job seekers use AI in their search, and nearly half admit to embellishing their credentials. By 2028, one in four candidates could be fake, with technology enabling AI-generated portfolios and even deepfake interviews.

So, how can you ensure you’re hiring a true expert? And what practical steps can you take to navigate this new reality? This guide explores actionable strategies for AI-driven hiring, featuring insights from industry leaders and AJ Zane, Director of Technology at NAMM, who shares proven methods for vetting technical talent and ensuring authenticity in the hiring process. By leveraging expert guidance and focusing on hands-on evaluation during interviews, hiring teams can confidently identify and secure the best candidates.

The problem: AI’s role in interview deception

AI’s growing presence in job applications is a double-edged sword. It streamlines tasks but also opens new paths for deception. Candidates can use AI to:

• Generate impressively polished responses—even to tough technical questions.
• Produce work samples or portfolios that may not reflect their own skills.
• Rely on real-time digital coaching, or even outsource interviews with deepfake assistance.

As Zane notes, “There are just so many tools now that someone who’s not an expert could use to still look like one on paper—or even in a video interview. It’s become part of the landscape.”

One report found that nearly a third of candidates now use AI to create fake work samples or automate applications. There have even been instances where applicants reportedly used AI or impostors during live interviews, and this challenge can sometimes even bypass screening processes when employers lack the tools or skilled technical evaluators.

As Zane puts it, “We used to say, if a candidate could ‘talk tech,’ that was good enough to get a foot in the door. Now, even that can be faked by AI. That’s why actually knowing what it takes to do the job—having built something, maintained systems, or led projects—matters more than ever.”

And the risks are more than hypothetical. According to findings from the U.S. Department of Labor, financial damages can range from $240,000 to $850,000 per fraudulent employee, often resulting from sophisticated scams, data breaches, or project failures tied to fraudulent hires.

Real stories from the hiring front line

Bringing in a technical evaluator during the interview stage can save significant time, money, and stress. Zane, part of Skill’s expert network, knows how challenging it is to distinguish between true talent and “AI deception” talent during interviews.

“Too often, hiring managers are expected to make technical judgments in unfamiliar roles. That’s where an expert network really shows its value,” he explains. “You might have a candidate who can describe every library or framework, but if they haven’t debugged real code or encountered complex customer needs, it shows up pretty quickly—if you know what to look for.”

He remembers interviewing one candidate: “Their resume was incredible. They had all the right answers. But when I asked for a specific example of a project going off the rails—what did they do, how did they communicate with other departments—the answers just looped back to generic jargon. That’s when you know you’re dealing with either a well-prompted AI or someone who hasn’t really been there.”

Zane draws a clear line: “There’s a world of difference between being able to rehearse a scenario and actually being able to solve problems when things break—because, in the real world, things always break.”

Solutions for smarter hiring

The right combination of AI-driven screening, precise candidate matching through machine learning, structured interviewing, and expert review significantly reduces the effectiveness of AI-enabled deception.

1. Verify the identity and authenticity of candidates

After AI-enabled screening and machine matching, the next crucial step is to confirm the authenticity of the candidate. This ensures you’re not wasting valuable interview time assessing the “skills” of a deepfake or imposter. At this stage, the focus should be on using technology and processes to filter out any obvious fraud.

• Implement digital ID verification: Utilize secure digital identity verification services that can cross-reference government-issued IDs with facial recognition technology, ensuring the person on screen matches their official documentation. At Skill, we are implementing this technology for every candidate we submit to clients.
• Look for inconsistencies in initial interactions: Even simple video calls can reveal red flags. Does the candidate’s audio lag unnaturally, or do their facial expressions seem “off”? Are there strange digital artifacts? While not conclusive, these can prompt further scrutiny.
• Consider deepfake detection: Consider deploying a tool designed specifically to analyze video and audio for deepfake characteristics (e.g., unnatural blinking patterns, voice inconsistencies, poor synchronization, unusual lighting).

2. Prioritize dynamic and unpredictable assessments

Once you’ve verified the candidate’s authenticity, you can then move to assessing their true capabilities. As AI becomes better at surface-level preparation, Zane advocates for live performance tests and collaborative challenges. “You need to see how someone thinks on their feet. That’s where you get past the script,” he says.

Practical examples include:

• Requiring a developer to debug or build something in real time, explaining each step.
• Having designers critique an unfamiliar product, with back-and-forth questions.
• Giving hypothetical “curveball” business scenarios mid-interview.
• Requesting the candidate to perform a simple, unexpected task, like holding up a specific number of fingers or briefly turning their head to the side (deepfake technology still struggles with real-time, unpredictable movements).

“AI can provide beautiful answers to simple, standard questions. But when the candidate is asked to connect the dots between strategy, design, and implementation—or to adapt when you change the requirements—that’s when experience and creativity show,” Zane adds.

3. Probe for depth, not just the right buzzwords

Fraudulent candidates often falter when interviewers probe into specifics. Even with extensive coaching, many fakes struggle to maintain their story when asked about details or the sequence of their work.

Zane recommends, “Go deeper. If someone claims to have architected a system, ask what tradeoffs they made, what failed, or which features they had to cut. Stories are hard to fake—especially the messy parts.”

4. Look for real soft skills—especially communication and adaptability

While AI helps candidates fake technical credentials, real people stand out for their collaboration and empathy. Soft skills are uniquely human—and in high demand across industries.

Zane shares, “I’ll intentionally ask candidates to explain technical decisions to a hypothetical non-technical manager or a client. The way they translate complexity, how they listen for the other person’s needs, is almost impossible to fake. Good technical people aren’t just coders—they’re connectors.”

He stresses, “When the project gets tough, you want the person who has actually worked through disagreements, changed course when something didn’t work, and helped lift the whole team’s game. These are the things AI doesn’t teach.”

5. Use a combination of AI screening tools and real human judgment

Even after initial checks, the ultimate success in hiring comes from blending technology with seasoned human insight. While AI can screen for red flags and verify basic information, it cannot replace the nuanced understanding of an experienced evaluator. This is especially important when the hiring team lacks experience in the role they are recruiting for, as they might miss critical technical or industry-specific cues.

“Machines can screen out obvious fraud, but they can’t replicate the gut feeling you get from having done the work yourself,” says Zane. “Expert evaluation isn’t just about technical tests—it’s about reading those nuanced cues and knowing what’s possible.”

For organizations hiring for high-stakes or technical roles, partnering with interviewers who’ve ‘walked the walk’ isn’t optional anymore—it’s crucial.

Why experts like Zane make the difference

Zane’s own career, which spans technology leadership at NAMM, startups, and consulting as a member of the expert network, has taught him that “bridging the gap between technical ability and real-world impact is everything.”

He recalls building cross-functional teams at NAMM: “It’s easy to hire for a checklist of skills, but much harder to find people who can grow with your business and adapt when new challenges show up. An expert in the evaluation process can spot who just checks the boxes versus who brings energy and solutions.”

As part of Skill’s Expert Network, Zane often reviews candidates for roles strikingly similar to his own. “Having someone who knows what the job is actually like—not just from a job description, but from living it day to day—shapes the whole interview and selection process,” he says. “I see my role as making sure teams aren’t fooled by surface-level knowledge—and that they’re excited about the real, hands-on skills their new hire will bring.”

Stay ahead with expert-backed hiring solutions

AI is raising the bar for both job seekers and hiring teams, making recruitment faster, but also more perilous if you don’t have the right expertise or network at hand. The risks of AI-enabled deception and costly mis-hires are very real, but so are the opportunities—if you know how to navigate them.

That’s why working with a partner like Skill can make all the difference. With direct access to AI deception best practices and technology combined with evaluators like AJ Zane—people who bring a blend of technical chops, real-world leadership, and an eye for authentic skill—you gain the competitive edge needed to hire with confidence.

Put simply: in a world transformed by technology, your success depends on the expertise behind your hiring decisions. Leverage modern screening tools, yes, but combine them with human judgment and proven experts for your most important roles.

Empower your recruiting with better, faster, and more cost-efficient solutions from Skill. As a next-generation staffing agency, we harness machine-matching technology and AI-powered recruiting to connect you with top talent and drive your business forward. Get in touch to discuss how we can solve your unique hiring challenges.