Job recruiters are meeting an uncanny new kind of candidate: the AI avatar. These digital humans mirror an applicant’s voice and likeness while being something else entirely, and they are turning up in first-round interviews. The phenomenon has become common enough that hiring managers are now developing new tactics to spot it, and many are retreating to old-fashioned face-to-face meetings to verify that the person on the screen is the person who will show up for the job.
Lana Kersanava, a Sydney-based recruiter, told Semafor she has encountered them over the past six months. “At the beginning, it’s like you feel like something is off,” she said, adding: “It looks very realistic.” That realism is exactly what makes the trend so challenging for employers, especially in high-volume hiring environments where first-round interviews are often brief and conducted over video. The technology has advanced to a point where the visual presentation is no longer the giveaway. Instead, it is the behaviour and language of the supposed candidate that raises the alarm.
How she spotted it
The tell was not the rendering, which held up. It was the answers, delivered with a polish that never faltered across a run of questions. Every response was perfectly structured, calmly paced and free of the natural hesitations, filler words and minor inconsistencies that characterise most human conversation. After roughly five minutes, Kersanava ended the interview and disqualified the candidate. She has now done this three times, and each case followed a similar pattern: the avatar was polished, coherent and entirely too smooth under pressure.
Recruiters who have dealt with these AI stand-ins say the interviews often feel scripted, even when the avatar is designed to respond dynamically to questions. There is no emotional nuance, no moment of genuine surprise, no subtle change in tone when a topic shifts unexpectedly. Instead, the avatar seems to be drawing from a prepared set of responses, and the result can feel like an automated customer service chat translated into video form.
The detail worth pausing on
All three avatar candidates had applied for English-speaking roles as non-native speakers, leaning on the technology to cover a gap in language proficiency. That is a different proposition from someone faking a work history. The candidates appear to be using avatars not to invent qualifications or employment records, but rather to overcome a communication barrier that might otherwise prevent them from even being considered for the position. It is a form of technological masking, and one that raises complicated questions about fairness, access and honesty.
It also lands in a hiring market with a documented bias problem. Research has found recruiters up to 19% less likely to follow up with job seekers from immigrant and ethnic minority backgrounds than with equally qualified candidates. In other words, non-native speakers may already face an invisible penalty when applying for roles in English-speaking countries, and some have turned to AI avatars as a workaround. None of which makes an undisclosed avatar acceptable. It does complicate the framing of these candidates as straightforward fraudsters, because their motive may be less about deception and more about equalising the playing field in a system that has historically favoured some applicants over others.
The system they are responding to
The rise of AI avatars in interviews does not happen in a vacuum. Applicant tracking systems already use AI to filter CVs before a human reads them, and recruiters increasingly deploy AI avatars to conduct first-round interviews themselves. In many large organisations, the initial screening process is fully automated: machines screen resumes, machines schedule interviews, and in some cases machines conduct the conversations. Candidates are now answering machines with machines.
The resulting AI-on-AI war is rewriting the hiring playbook, pushing employers towards live technical walk-throughs, scenario challenges, and roleplay simulations that are harder to automate through. These methods force the candidate to demonstrate actual skill in real time, which is much more difficult to fake with an avatar or a language model. Some companies have started using video verification tools that require candidates to look directly into the camera and perform specific tasks, while others have moved to live coding exercises and problem-solving sessions that cannot be prepared in advance.
The volumes explain the arms race. Nearly two-thirds of candidates now use AI in applications and 87% of US hiring managers use it in hiring, alongside a 239% surge in AI-generated applications. The sheer scale of AI involvement means that both sides of the hiring table are relying on automated tools to gain an advantage, and the result is a growing game of cat-and-mouse that shows no signs of slowing down.
How common this is
The trend is not marginal. A 2026 Greenhouse report found 91% of US hiring managers have encountered or suspected AI-generated answers during online interviews. Across 19,368 live interviews analysed between July 2025 and January 2026, 38.5% of candidates were flagged for AI-assisted behaviour. That is a striking figure, and it suggests that a substantial share of remote interviews now involve some form of artificial assistance, whether that is a fully automated avatar or a human closely reading scripted answers generated by an AI tool.
The trajectory points one way. Gartner projects that by 2028 one in four job candidate profiles globally will be fake, spanning AI-generated profiles, deepfake video interviews, and fabricated work histories. Barriers to entry are minimal. Palo Alto Networks found it takes as little as 70 minutes for someone with no image manipulation experience to build a fake candidate capable of passing a video interview. The tools required are widely available, and many of them are free or low-cost, meaning that virtually any applicant can create a polished digital version of themselves with minimal technical skill.
What is more, the rapid adoption of generative AI in everyday life has normalised the use of these tools. Candidates may not view an AI avatar as malicious deception, but rather as a natural extension of the assistance they already use to write resumes, craft cover letters and prepare for interview questions. The line between “AI-assisted preparation” and “AI-impersonated presence” is blurring, and recruiters are left to draw the boundary on a case-by-case basis.
Employers are retreating to the room
Seventy-two per cent of recruiting leaders now run at least one in-person stage specifically to counter AI-assisted fraud, with Google, McKinsey, and Cisco reintroducing mandatory face-to-face rounds. The logic is simple: no avatar, deepfake or AI script can stand in for a person who is physically present in a meeting room. In-person interviews allow interviewers to assess body language, spontaneous reactions, and the kind of interpersonal chemistry that is difficult to replicate digitally.
That solves detection at the cost of everything remote hiring was meant to deliver. Candidates who cannot travel, including many of the international applicants this technology most tempts, lose access first. The shift back to in-person stages effectively reverses the flexibility that remote hiring introduced, and it disproportionately affects people who live outside major hiring hubs or who cannot afford the time and expense of travelling to an office for one round of interviews. For those candidates, the in-person requirement becomes a barrier that no amount of AI sophistication can overcome.
A number of companies are also investing in detection software that claims to identify deepfake video interviews. These tools analyse micro-expressions, voice patterns and even the subtle movements of a person’s eyes and head to determine whether the image is being generated in real time. Yet these detection systems are far from perfect, and they can produce false positives, incorrectly flagging candidates who simply have an unusual speaking style or a poor connection. The arms race between detection and generation is ongoing, and there is no clear end in sight.
The screening was never that good
There is an awkward premise underneath the panic, which is that the automated filtering being defended works. The case against AI CV screening has been made repeatedly and forcefully, largely on the grounds that it optimises for keyword matching rather than capability. Traditional applicant tracking systems are famously easy to game: adding the right buzzwords to a resume can substantially increase its chances of being seen by a human recruiter, regardless of whether the candidate actually has the relevant experience. The result is that many qualified candidates are screened out while others who are better at writing resumes, not doing the job, move forward.
Candidates optimising against that filter with better tools is a predictable outcome rather than a moral collapse. Kersanava’s five-minute detection rate also suggests the current generation of avatars is not fooling attentive humans. In each of her three cases, the avatar was uncovered relatively quickly, which implies that the technology, while realistic in appearance, still lacks the behavioural authenticity that makes a conversation feel genuine. A sharp interviewer who knows what to listen for can often tell within minutes that something is off.
What it is doing is making the first round worthless for everyone. If the machine screens the machine, the interview stops measuring anything, which is an argument for changing the process rather than policing the candidates. The broader lesson may be that the industry placed too much faith in automated screening and remote interviews without considering how quickly the same technological advances would be turned around and used by applicants. Instead of trying to build ever-stronger filters and detection systems, employers might be better served by redesigning the early stages of hiring to focus on direct demonstration of skills, peer collaboration, and substantive problem-solving. Those methods are harder to fake, and they measure qualities that are actually relevant to job performance.
The rise of AI avatars in job interviews is not only a story about deception or technology. It is also a mirror reflecting the limitations of the hiring systems that organisations have built. As the arms race between AI-assisted candidates and AI-assisted recruiters continues, the fundamental question remains: what is a first-round interview supposed to measure? If it is merely a test of whether someone can perform well in a scripted conversation, then an AI avatar is just another actor on the stage. If it is meant to reveal something deeper about a person’s ability to think, communicate and collaborate, then the process itself needs to be reimagined in a way that no avatar, however realistic, can easily defeat.