But when she started to apply for full-time jobs, all she heard back — on the rare occasions she heard anything — was that roles were being cut, either because of AI or outsourcing. Before pausing her job search recently, McMahon had applied to roughly 150 jobs. “I know those are kind of rookie numbers in this environment,” she said jokingly. “It’s very discouraging.”
McMahon’s frustrations are pretty typical among job seekers freshly out of college. There were 15 percent fewer entry-level and internship job postings in 2025 than the year before, according to Handshake, a job-search platform popular with college students; meanwhile, applications per posting rose 26 percent. The unemployment rate for new college graduates was 5.7 percent in December, more than a full percentage point above the national average and higher even than what high-school graduates face.
How much AI is to blame for the fragile entry-level job market is unclear. Several research studies show AI is hitting young college-educated workers disproportionately, but broader economic forces are part of the story, too. As Christine Cruzvergara, Handshake’s chief education-strategy officer, told me, AI isn’t “taking” jobs so much as employers are “choosing” to replace parts of jobs with automation rather than redesign roles around workers. “They’re replacing people instead of enabling their workforce,” she said.
The fact that Gen-Z college interns and recent graduates are the first workers being affected by AI is surprising. Historically, major technological shifts favored junior employees because they tend to make less money and be more skilled and enthusiastic in embracing new tools. But a study from Stanford’s Digital Economy Lab in August showed something quite different. Employment for Gen-Z college graduates in AI-affected jobs, such as software development and customer support, has fallen by 16 percent since late 2022. Meanwhile, more experienced workers in the same occupations aren’t feeling the same impact (at least not yet), said Erik Brynjolfsson, an economist who led the study. Why the difference? Senior workers, he told me, “learn tricks of the trade that maybe never get written down,” which allow them to better compete with AI than those new to a field who lack such “tacit knowledge.” For instance, that practical know-how might allow senior workers to better understand when AI is hallucinating, wrong, or simply not useful.
For employers, AI also complicates an already delicate calculus around hiring new talent. College interns and recent college graduates require — as they always have — time and resources to train. “It’s real easy to say ‘college students are expensive,’” Simon Kho told me in an interview. “Not from a salary standpoint, but from the investment we have to make.” Until recently, Kho ran early career programs at Raymond James Financial, where it took roughly 18 months for new college hires to pay off in terms of productivity. And then? “They get fidgety,” he added, and look for other jobs. “So you can see the challenges from an HR standpoint: ‘Where are we getting value? Will AI solve this for us?’”
Weeks after Stanford’s study was released, another by two researchers at Harvard University also found that less experienced employees were more affected by AI. And it revealed that where junior employees went to college influenced whether they stayed employed. Graduates from elite and lower-tier institutions fared better than those from mid-tier colleges, who experienced the steepest drop in employment. The study didn’t spell out why, but when I asked one of the authors, Seyed Mahdi Hosseini Maasoum, he offered a theory: Elite graduates may have stronger skills; lower-tier graduates may be cheaper. “Mid-tier graduates end up somewhat in between — they’re relatively costly to hire but not as skilled as graduates of the very prestigious universities — so they are hit the hardest,” Maasoum wrote to me.
Just three years after ChatGPT’s release, the speed of AI’s disruption on the early career job market is even catching the attention of observers at the highest level of the economy. In September, Fed chair Jerome Powell flagged the “particular focus on young people coming out of college” when asked about AI’s effects on the labor market. Brynjolfsson told me that if current trends hold, the impact of AI will be “quite a bit more noticeable” by the time the next graduating class hits the job market this spring. Employers already see it coming: In a recent survey by the National Association of Colleges and Employers, nearly half of 200 employers rated the outlook for the class of 2026 as poor or fair, the most pessimistic outlook since the first year of the pandemic.
The upheaval in the early career job market has caught higher education flat-footed. Colleges have long had an uneasy relationship with their unofficial role as vocational pipelines. When generative AI burst onto campuses in 2022, many administrators and faculty saw it primarily as a threat to learning — the world’s greatest cheating tool. Professors resurrected blue books for in-classroom exams and demanded that AI tools added to software be blocked in their classes.
Only now are colleges realizing that the implications of AI are much greater and are already outrunning their institutional ability to respond. As schools struggle to update their curricula and classroom policies, they also confront a deeper problem: the suddenly enormous gap between what they say a degree is for and what the labor market now demands. In that mismatch, students are left to absorb the risk. Alina McMahon and millions of other Gen-Zers like her are caught in a muddled in-between moment: colleges only just beginning to think about how to adapt and redefine their mission in the post-AI world, and a job market that’s changing much, much faster.
What feels like a sudden, unexpected dilemma for Gen-Z graduates has only been made worse by several structural changes across higher education over the past decade.
by Jeffrey Selingo, Intelligencer | Read more:
Image: Intelligencer; Photos:Getty
