Anne Hathaway says she can spot the difference when a job candidate lets ChatGPT do the work.
While hiring for a recent role, Hathaway said she received thank-you notes from every candidate, and every one was AI-written and identical. 'They were all the exact same thank you note,' she said in an interview with Hits Radio. When the first note arrived, she thought, 'How nice, how professional.' After the others landed word-for-word the same, she realized, 'Oh, no ... I see something I’m not supposed to see.'
Her warning was simple: 'If you’re out there thinking that you’re getting away with something, there’s a chance that you might be revealing yourself.'
Meryl Streep, who also sat in on the interview, made the hiring logic plain. 'That’s just tragic,' she said of AI-written thank-you notes. 'Nobody on that list gets that job.'
The episode lands in a labor market that Fortune describes as uncertain, with AI-driven redundancies and what it called the worst job market in 37 years. For candidates applying to hundreds of jobs, the temptation to automate is obvious. But the market has already voted on what that shortcut looks like: generic, identical language reads less like effort and more like indifference.
That matters because hiring is still a competition for attention. A thank-you note can be a small signal, but it is one of the few that costs almost nothing except time and judgment. When every applicant uses the same tool with the same prompt, the result is not efficiency. It is sameness.
Fortune also noted that the thank-you note itself has become contentious, with some arguing that candidates are being asked to do free work on top of multiple-stage interviews, aptitude tests and even secret personality assessments. But the practical reality remains unchanged: in a crowded market, the small human details still matter.
Sophie Rocha, who works in marketing for the Gen Z careers platform Home From College, said it takes 'two seconds' to send a thank-you note and that people are not doing it often enough to stand out.
For free enterprise, the lesson is older than ChatGPT. Capital rewards clear signals, not lazy ones. In a hiring process, the candidate who shows judgment, effort and individuality is still the candidate most likely to earn trust.
Automation can help productivity. It can also flatten the very traits employers are trying to measure. When the note looks copied, the applicant looks copied too. In a market where every edge matters, that may be the most expensive shortcut of all.
