A new study from Resume Genius finds that while artificial intelligence has become a standard part of recruiting, employers remain concerned about applicants using the same tools on their applications.
Resume based on Genius AI Impact on Employment Report in 2026 According to a Pollfish survey of 1,000 U.S. hiring managers and recruiting team members. The survey examined employers’ use of AI, their experience with AI-powered candidate materials, and their perceptions of AI’s impact on recruitment.
The report found that 87% of recruiters use AI in at least one stage of recruitment. The most common application was a resume review, reported by 58 percent of respondents. This was followed by creating and posting job descriptions at 46 percent, matching candidates to roles at 44 percent, and scheduling interviews at 41 percent.
At the same time, 82% of recruiters say they are concerned about candidates using AI in their job search, and 86% expect AI to make it harder to determine whether an application accurately reflects a candidate’s abilities.
AI creates an authenticity gap
Most respondents said they had encountered signs that AI candidates were being used. 58% reported receiving an AI-generated resume or cover letter, 46% said they had encountered a candidate who used AI to answer interview questions, and 34% said they had seen an AI-generated LinkedIn or other social media profile. 29% reported portfolio work generated by AI, and 28% said candidates used AI to cheat on skill assessments.
17% of recruiters also reported encountering deepfake technology during video interviews. However, the report does not provide details on how employers identified or verified these incidents.
Employers reported confidence in AI’s potential to improve their processes. 72% said it could make hiring faster and more efficient, 68% said it could help identify better candidates, and 65% said it could help reduce hiring bias.
Transparency remains unstable. 35% of respondents said their organization always discloses the use of AI during interviews and candidate evaluations, while 26% said it only sometimes. 20% said their organization does not currently disclose their AI usage, and 12% said they have no plans to do so publicly.
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Evaluate candidates through direct evidence
Eva Chan, career expert at Resume Genius, says that rather than discouraging applicants from using AI, employers should address concerns about reliability by changing the way they evaluate applicants.
“Employers can’t have it both ways. Employers are using AI to screen resumes and create job postings, so they need to allow candidates to use AI as well,” Chan said. “The real problem is that employers can no longer distinguish who a person is on paper, and that’s a legitimate concern. But the answer isn’t to ask candidates to stop using the tools that employers rely on them to be. If you want to know, you need to change the way you evaluate people. That means live problem solving, structured interviews, and real work samples. This is something that employers need to fix, not candidates.”
Applying direct assessment to laboratory recruitment
For laboratory employers, Chan’s recommendations provide a practical framework for evaluating candidates through direct job-related evidence. Rather than relying on predictable questions that candidates can rehearse, hiring teams can present realistic scenarios and ask applicants to explain how they would answer. Using the same scenarios, follow-up questions, and scoring criteria for all candidates allows interviewers to consistently compare answers and focus on how applicants process information, structure decisions, and troubleshoot operational issues.
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The evaluation should reflect the responsibilities of the position. Examples of suggestions include:
- Interpreting anonymized quality control trends
- Check out a short excerpt of our Standard Operating Procedures (SOP)
- Explain how to respond to equipment failure
- Prioritizing work in the sample backlog
For roles that require specific bench skills, employers may also use supervised work samples or technical demonstrations and request references to confirm the candidate’s proficiency with specific methods, equipment, or software.
Hiring teams can also assess safety awareness by having candidates walk through routine testing procedures from start to finish without specifically asking about safety. Their answers will reveal whether they naturally incorporate personal protective equipment, hazard identification, waste disposal, and other safety considerations into their workflows. Rather than relying on conversational chemistry or a general impression of a “fit,” interviewers can also assess traits such as accountability, curiosity, and receptivity to feedback through targeted behavioral questions.
These practices place the responsibility back on the employer to design a hiring process that assesses the competencies that the laboratory actually needs. As AI facilitates the creation and refinement of application materials, in-person assessments can provide strong evidence of how candidates think, approach, and respond to realistic laboratory conditions.
This article was created with the assistance of Generative AI and underwent editorial review before publication.
