The House Subcommittee on Higher Education and Workforce Development held a hearing on June 3 to discuss how artificial intelligence is reshaping higher education institutions and their approach to preparing students for the AI-driven economy.
The discussion featured witness testimonies from industry leaders across higher education and centered on an overwhelming sentiment: As students enter the workforce and attain entry-level roles, they need to be adequately equipped with foundational AI skills, or risk being left behind.
For HR leaders, the hearing underscored the growing reality that employers increasingly expect AI proficiency from workers of all skill levels, including entry-level workers just graduating from universities.
Experts Warn Against both Overreliance and Restriction
In a witness statement from Dave Duke, chief product officer for higher education at McGraw Hill, one of the most consequential challenges facing higher education is that students are already using AI tools heavily through daily use without learning how to evaluate AI-generated outputs or apply the technology responsibly within professional settings.
Duke warned that at the same time, some institutions are responding primarily through “restriction and detection,” producing graduates who see AI as “something to be managed and avoided rather than understood and used with skill and judgment.”
That tension mirrors debates unfolding inside workplaces as employers balance AI-driven productivity gains with concerns around overreliance on AI tools.
Witnesses Stress the Importance of Critical Thinking Skills
Much of the discussion centered around students retaining critical thinking skills. Jonathan Fozard, chief information officer at Florida State University, emphasized keeping human judgment at the center of AI.
“We have to use critical thinking skills to be able to determine and differentiate fact from fiction,” he said. “If we view AI through this lens of being the sole source of truth, we negate the human aspect.”
Witnesses also emphasized that colleges may need to fundamentally rethink how learning is measured as AI becomes more capable of completing traditional assignments.
“If AI can complete an assignment, perhaps the assignment itself is in need of change,” said Michael Horn, an adjunct professor at the Harvard Graduate School of Education. He argued that institutions should move toward more presentations, demonstrations, oral defenses, and work-based learning experiences embedded with AI that better reflect real-world AI-enabled environments.
Uneven AI Access Could Shape Future Talent Pipelines
The hearing also highlighted growing concerns about unequal access to AI tools and training — an issue HR leaders may increasingly encounter in recruiting and talent pipelines.
Bridget Burns, CEO of the University Innovation Alliance, warned that under-resourced institutions could fall behind wealthier universities with stronger vendor partnerships and larger technology budgets.
“If we’re not careful, AI could become one more area where well-resourced institutions move forward, while under-resourced institutions are asked to do more with less,” she said.
Witnesses pointed to several examples of institutions already integrating AI into workforce preparation, including AI literacy graduation requirements, AI-powered tutoring tools, and partnerships with tech companies to expand student access to AI platforms and training.
Ultimately, the hearing’s broader message was that AI readiness is becoming a core workforce competency, and individuals — especially those entering the workforce — risk falling behind without that competency.
"We must treat AI literacy as a national workforce priority,” Fozard said. "We must support secure and responsible access to AI tools, so that students are prepared for the future ... We must invest in hands-on learning and workforce development programs.”
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