Universities Should Not Become Links in the AI Supply Chain

This year's graduation season in the U.S. featured numerous speakers praising artificial intelligence (AI) as a key to solving all problems. However, the response from new graduates was not always positive, with many booing in protest of this message.

Students are leaving school at a time when AI is promoted not only as a necessary tool but as a force that can transform the labor market. The challenge extends beyond employment issues: universities are also encouraged to restructure around AI, seeing it as a solution for budget pressures, administrative burdens, and employer demands.

The real risk lies in universities becoming victims of an uncritical embrace of AI, especially during financial difficulties. Stakeholders in the tech industry have strongly encouraged this trend.

A report funded by Cisco argued that 'forward-thinking' educational institutions view AI as a solution for resource constraints. The report emphasized that AI can automate routine tasks, improve student services, and help institutions operate more efficiently. Notably, it asserted that universities must accept a 'role as a link in the AI skills supply chain,' as students expect AI integration and employers increasingly demand AI knowledge.

Many schools have adopted this logic. The University of Minnesota, Dartmouth College, and Syracuse University have signed agreements with AI companies. In 2025, California State University (CSU) reached a $17 million deal with OpenAI to provide an 'education-focused' chatbot to over half a million students and faculty.

Although surveys show many CSU faculty and students remain unconvinced by 'AI's flashy promises,' the deal was seen as a turning point. For OpenAI, signing with the largest public university system in the U.S. demonstrates its ability to deploy AI at scale. For CSU, it represented 'a massive branding opportunity.' Despite facing a budget cut of about $144 million, CSU recently extended the deal on more expensive terms, committing $13 million per year for three years, totaling roughly $39 million.

A small but notable example occurred at Glendale Community College (GCC) in Arizona. The administration used an AI system to read student names as they received diplomas. The system failed to match names to students, causing names on the big screen to not correspond with the graduates. President Tiffany Hernandez was booed when explaining the glitch. One graduate said the apology 'didn't seem sincere.'

The issue becomes more serious when AI enters teaching and assessment. A study led by a University of Cambridge team found that AI often undervalues 'essays that human judges rated highest' and overvalues essays based on length, vocabulary, and sentence complexity—factors often unrelated to academic standards. Deborah Talmi, the study lead, warned that using AI in assessment risks educational values.

Critics warn of an 'AI bubble,' where profits depend on AI being widely adopted, everywhere, at an unprecedented pace. Universities are particularly valuable in this project: they lend AI companies legitimacy, scale, and access to the future workforce. The problem is that schools are being treated as cogs in a machine that generates profits for Big Tech.

The lesson from the boos of graduates is a refusal to accept a system that treats them as workers to be prepared, data to be processed, and consumers to be managed, rather than students to be educated. In the 'AI era,' this is the university's mission that educators, students, and the public must defend.