May 16, 2026
New York Post recently published an article featuring Emma Wiles, Isabel Anderson Career Development Professor, Information Systems, discussing how AI-powered applicant tracking systems may favor resumes generated by the same large language models they use to evaluate candidates, creating a potential new source of bias in hiring.
Researchers found AI screening tools were 23% to 60% more likely to advance candidates whose resumes were written by the same AI model, raising concerns that qualified applicants could be overlooked.
The findings suggest hiring systems may be rewarding familiarity rather than talent. “Instead of AI tools being used to find the applicant’s true abilities, you’re gonna find applicants that the AI thinks sounds like itself,” Wiles adds.
Wiles advises job seekers to use AI to refine their writing rather than replace it entirely, helping ensure their authentic skills and experiences remain visible throughout the hiring process.
