Employers are demanding more years of experience for fewer entry-level roles, and the rapid adoption of AI tools is making it even harder for new graduates to break into tech.
Laura Ullrich, who oversees economic research at Indeed, has a front-row seat to a generational crunch in the hiring market. Her own son is graduating this year with a master’s degree in data science, and the landscape he faces is unforgiving. “It’s brutal out there right now,” she told Fortune. She hears the same anxiety from parents and recent graduates who regularly ask her for guidance. The data backs up their concern. The unemployment rate for recent college graduates, those between 22 and 27 years old, climbed to roughly 5.7% in the fourth quarter of 2025. That figure sits well above the 4.2% rate for all workers and the 3.1% rate for college graduates of all ages, based on figures tracked by the Federal Reserve Bank of New York.
Part of the problem is a dynamic Ullrich calls “experience creep.” Employers, armed with more leverage in a cooling labor market, are steadily raising the experience bar for positions that once welcomed fresh graduates. According to Indeed’s job posting data, the share of listings open to candidates with two to four years of experience fell from 46% in mid-2022 to 40% by mid-2025. Over the same period, the share of postings requiring at least five years of experience climbed from 37% to 42%. When supply of labor outstrips demand, companies can afford to be picky. If you can hire someone with four years of proven work history for the same price as a rookie, the rational business move is obvious.
But this isn’t just a standard employer’s market cycle. The rise of generative AI is compounding the problem in ways economists are still working to untangle. A November report from Stanford economists found substantial declines in employment for early-career workers aged 22 to 25 in occupations most exposed to AI, including software development and customer service. Overall employment, meanwhile, kept growing. The findings suggest generative AI has crossed the threshold from theoretical disruption to measurable impact on entry-level hiring.
The question researchers are wrestling with is whether AI is directly replacing workers or whether the massive capital poured into AI infrastructure is crowding out payroll budgets. Ullrich suspects it’s largely the latter right now. Companies are plowing billions into data centers, computing power, and model training. That spending has to come from somewhere, and headcount is often the first place finance teams look. Oracle, for example, laid off scores of workers in the same week it committed to massive capital investments in AI infrastructure. This pattern, trading labor costs for capital expenditure, is a familiar feature of technological transitions. What makes this one different is that AI tools can genuinely perform some of the grunt work that has traditionally served as on-the-job training for junior employees.
A pipeline problem in the making
The tech sector is feeling this squeeze more acutely than most. Job postings for software developers on Indeed are down 29% from pre-pandemic levels. Data and analytics roles have dropped 38%. Companies that do hire can bring in experienced engineers at rates that would have been unthinkable three years ago, a short-term win for their recruiting budgets.
The long-term risk, however, is a broken talent pipeline. Growth in tech employment is concentrated at senior levels. If companies stop hiring and training junior developers because AI handles the baseline tasks, where will the next generation of senior engineers come from? It’s a structural question that CEOs will eventually have to answer. Anthropic’s Dario Amodei has publicly predicted that AI could eliminate large swaths of entry-level work. If he’s even partially right, the experience creep we’re seeing today is not a temporary market correction. It’s the leading edge of a permanent reshaping of how technical careers begin.
For startups and established firms alike, the implication is straightforward. Saving money on junior hires today may well create a expensive talent shortage tomorrow. The companies that figure out how to integrate AI productivity gains while still investing in early-career development will have a meaningful competitive advantage when the senior talent pipeline inevitably thins out. Watch which companies start building apprenticeship-style programs designed around AI-augmented workflows. That’s where the next wave of talent strategy is heading.