Lawmakers wrestle with AI’s opportunities, challenges in higher education

As with many areas of society, higher education institutions are wrestling with the impact of artificial intelligence, both on students’ learning and their faculties’ teaching.

Supporters said during a recent House subcommittee hearing that AI can help accomplish various tasks, encouraging colleges and universities should embrace the technology and establish policies for its responsible use. But even its supporters acknowledged there are a lot of obstacles ahead, including AI’s potential for use in academic cheating and the potential to widen the digital and resource divides that already exist.

Still others said that, unless academia fundamentally reimagines its processes and priorities, AI will not bring about the massive revolution its supporters have promised, making for a challenging time as lawmakers and academic leadership try to find a path forward.

“The right response [to AI] is neither knee-jerk prohibition, nor careless adoption,” Rep. Burgess Owens, a Utah Republican who chairs the House Education and Workforce Committee’s Subcommittee on Higher Education and Workforce Development, said in his opening statement. “It is thoughtful leadership, grounded in a commitment to student success. Some institutions are already demonstrating what that looks like with AI literacy initiatives, faculty development programs, and partnerships with employers designed around evolving workforce needs.”

Recent research has suggested that AI’s future in higher education remains uncertain, even as adoption has skyrocketed. Both a national Gallup poll and a statewide one for California State University found widespread use of AI, but many respondents noted a lack of clear guidance on how to use it safely and responsibly.

That lack of clear guidance, uncertain areas of responsibility around this new technology and no place to share best practices can make moving forward even more challenging, experts said.

“Most institutions are not resisting AI,” Bridget Burns, CEO of the University Innovation Alliance, a national consortium of 19 public research universities, said in written testimony. “But most are navigating it alone. Right now, thousands of these conversations are happening across higher education: legal reviews, procurement negotiations, classroom experimentation, faculty governance discussions, but with very few mechanisms to accumulate and share what institutions are learning.”

Others said the federal government should play a stronger oversight role. Rep. Alma Adams, a North Carolina Democrat and the subcommittee’s ranking member, said current federal AI policy is “moving us in the wrong direction,” including by cutting jobs at the Department of Education and its Office of Civil Rights.

“We need strong guardrails and infrastructure that match the scale of this technological shift,” Adams said in her opening statement. “And that means restoring and strengthening federal educational technology leadership. It means rebuilding OCR's capacity so that complaints involving AI discrimination and data misuse can actually be investigated. It means establishing clear accountability standards around transparency, data protection, auditing, and oversight for AI systems used in higher education. Most importantly, higher education institutions need coordinated federal guidance instead of being left to navigate this alone, campus by campus.”

Burns warned too that resource gaps could prevent some universities from truly taking advantage of AI and helping students use it responsibly, and so it could “unintentionally widen the gap between well-resourced and under-resourced institutions and further the digital divide we are already seeing emerge.” 

AI should not be something that only advantages a small concentration of institutions, she said, otherwise it will be harder to attract talent.

“The campuses with the most resources will move faster, attract more expertise, negotiate stronger vendor agreements, develop governance frameworks, and build AI literacy programs,” Burns said. “Meanwhile, institutions with fewer resources are often being asked to navigate the same challenges with significantly less capacity. Whether a student benefits from responsible AI adoption should not depend on where they happen to enroll.”

Burns pointed to the likes of Arizona State University, Purdue University, the University of California at Riverside and the University of Utah as examples of institutions that are embracing AI, whether it be by using it to help make the credit transfer process more efficient, integrating AI literacy or designing tools and guides to help students better understand how it can be used.

But Michael Horn, an adjunct professor at the Harvard Graduate School of Education, warned that many institutions are like early factories, which he said, “replaced steam engines with electric motors but saw little productivity gains because they kept the same organizational designs and processes.”

“Only later, when factories redesigned themselves around electricity, did productivity surge,” he added in written testimony. To do that, Horn suggested embracing AI to boost academic rigor and raise expectations of the work students can produce, as he argued that, if today’s assessments can be passed by the technology, maybe they need a rethink. Horn also said AI could help connect data on academic performance, finances and well-being to help give students more meaningful support.

Lawmakers said a lot of work lies ahead if higher education is to successfully embrace AI. Doing so, they said, will mean the United States remains globally competitive.

“We should welcome this inevitable reality — technology has changed how the world works since the horse and buggy,” said Rep. Randy Fine, a Florida Republican. “We didn’t look back; we looked forward and that’s what we need to do here as well. Our education system has a challenge — to prepare [our students] for reality, not train them for the jobs that will no longer exist.”