As artificial intelligence automates the work college once prepared students to do, experts warn that the very concept of a traditional university education is under threat, forcing institutions to rethink their role in shaping careers and providing real world skills.
Well before the term AI had entered the evening news, the traditional model of higher education in the United States was already in jeopardy. Between 2010 and 2022, the year ChatGPT launched, university enrollment dropped nearly 15 percent, according to federal data. State funding cuts pushed tuition costs even higher, leaving many students questioning whether the enormous investment of time and money was worth the credential.
The arrival of AI in the workforce has intensified that uncertainty. Fresh graduates now face the stark reality that their degrees often do not translate into stable, well compensated jobs. Algorithms and machine learning systems are performing tasks once reserved for entry level workers, eroding the very market universities have historically prepared students to enter.
Alina McMahon, a recent graduate of the University of Pittsburgh, told New York Magazine that the job market for her cohort is grim. After applying to roughly 150 full time positions, her only feedback was that many roles had been cut entirely. She described the numbers as rookie figures in this environment, calling the situation very discouraging.
Data from the Federal Reserve Bank of New York shows the unemployment rate for recent college graduates jumped to 5.8 percent in the first quarter of 2025, the highest reading since 2021. This rate is nearly two percentage points higher than the national average, with recent graduates facing unemployment at almost double the rate of all college degree holders, which hovers around 2.9 percent.
Traditional pathways into the workforce, such as internships and entry level programs, are also disappearing. Simon Kho, the former head of early career programs at Raymond James Financial, explained that it often took 18 months for a new graduate to become fully productive. At around that point, they get fidgety and begin searching for the next step in their career, he said, noting the challenges from a human resources standpoint which leads to uncomfortable questions about where value is being generated and whether AI will solve the problem.
The effect on colleges is immediate. If students cannot secure internships, especially in fields like computer science or finance, their degrees lose practical value. Fewer opportunities for applied experience are translating into shrinking class sizes and waning enrollment in programs once considered essential for the modern economy.
Ryan Craig, author of Apprentice Nation and managing director at Achieve Partners, told New York Magazine that colleges and universities face an existential issue before them. They need to figure out how to integrate relevant, in field, and hopefully paid work experience for every student, and hopefully multiple experiences before they graduate.
The stakes extend beyond financial returns. Experts note that the shift reshapes students’ career expectations and their confidence in the system. For example, tech majors once encouraged to learn to code are finding that coding skills alone no longer guarantee employment. AI driven tools are performing basic programming tasks, automating data analysis, and even drafting routine technical reports. The practical differentiation students once gained through college projects is now often matched or surpassed by software.
Meanwhile, industries across finance, consulting, media and research are recalibrating the need for junior staff. More than 400 tech employers including Meta, Intel and Cisco announced over 130,000 job cuts in 2025, according to tech job site TrueUp. Internships that once served as pipelines for talent are being replaced with AI driven training programs or eliminated altogether. Employers increasingly question whether the investment in human capital is worth the time, particularly when AI systems can perform similar functions more quickly and at lower cost.
Craig argues that generative AI is likely to narrow the skills gap while turning the experience gap into a chasm. Entry level workers no longer need to perform repetitive menial tasks that have been automated by AI, but are instead expected to make decisions and exercise judgment like people who have been on the job two or three years. The question becomes how to close that experience gap when entry level positions that once provided that training are disappearing.
As the first generation of digital natives enters higher education, the pressure on universities intensifies. They are being asked to prepare students not just with academic knowledge but with the real world, hands on experience that AI has rendered more difficult to acquire. Craig argued that universities must innovate aggressively to survive, integrating work experience, mentorship and applied skills into the curriculum in a way that ensures graduates are employable.
Some universities are experimenting with partnerships with tech companies to provide real world projects, while others are exploring AI literacy as a core competency. Yet these efforts often struggle to keep pace with the rapid evolution of AI capabilities. The disconnect between academic preparation and market expectations is growing, leaving many students feeling unmoored.
NBC News collected more than 100 responses from recent graduates describing months spent searching for jobs, hundreds of applications and zero responses from employers, even with degrees once thought to be in high demand like computer science or engineering. Some said they struggled to get an hourly retail position or are making salaries well below what they had been expecting in fields they had not planned to work in.
For students like McMahon, the uncertainty is tangible. Even highly motivated graduates with strong grade point averages are navigating a job market in which AI performs tasks that previously justified years of study. The return on investment for a college degree, already under scrutiny before ChatGPT, now faces unprecedented pressure.
Craig emphasized that the model of higher education as a ticket to a professional career is under siege. Institutions must rethink their approach to learning, skill building and workforce integration, or risk becoming obsolete. In the first half of 2024, more than one college a week announced that it would close, reflecting the financial pressure facing institutions unable to adapt.
The crisis extends beyond individual institutions to national economic competitiveness. The United States was second among developed nations in 25 to 34 year olds with bachelor’s degrees in 2000, and now ranks 16th. The Top 15 developed nations, on average, have increased bachelor’s degree attainment by 177 percent during that time.
Concerns about AI automation of entry level positions traditionally filled by college graduates have compounded these worries, especially since poor job market outcomes early in life can translate into persistent earnings shortfalls over the course of a career.
The challenge facing higher education is no longer simply about improving quality or reducing costs. It is about fundamentally reimagining what a university degree should provide in an age when artificial intelligence can replicate many of the technical skills that once required years of formal study. For millions of students and their families, the question is increasingly urgent: what is college for in the age of AI?
