OPINION: Knowing how to use AI tools is not the same as knowing how to apply them responsibly. Colleges must do more

by Ngoc Cindy Pham, The Hechinger Report
August 31, 2026

Universities across the country are investing in artificial intelligence literacy. Students are attending workshops, experimenting with generative AI tools and earning certificates meant to show that they are ready for an economy shaped by AI.

The problem is that we don’t know if these programs help students solve workplace problems, if they open doors to job opportunities, or both. We also don’t know if they give students from different institutions a fair chance to compete.

Higher education has an AI pilot program problem. Much of the evidence for “successful” programs still comes from single-region studies and relies on short-term measures such as test scores and self-reported data. Too often, they are described as successful before anyone can show whether students have actually used what they learned beyond the classroom.

Colleges should stop treating AI literacy as the finish line and start building clear pathways from learning to workplace application. Every AI literacy program should be designed with employers, tested across institutions and evaluated by what students can actually do afterward. Attendance, certificates and satisfaction are not enough. The goal must be readiness.

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AI literacy is necessary. Still, just knowing how to use a tool does not mean a student knows how to apply it responsibly to an unfamiliar workplace problem. A student may know how to ask a chatbot a question without knowing how to check the answer, protect private information, explain a recommendation or decide when the tool should not be used. Those abilities develop through repeated practice in real contexts. That is why colleges and universities should adopt shared measures of AI workforce readiness.

The stakes are especially high for students at public and less-resourced institutions. They may be introduced to AI tools without receiving enough practice, guidance or employer connections to turn that introduction into an opportunity.

Earlier this year, I founded an initiative to examine this challenge across two different settings. The program brought CUNY undergraduates and NYU Tandon graduate engineering students into the same hands-on series of workshops. Industry professionals showed students how AI is used in actual jobs, and students practiced using the tools for workplace tasks and explaining their decisions.

Our small, preliminary study found that the two groups reached similar levels of applied AI use. Participation emerged as the clearest factor in predicting that use. Among students who attended one or two workshops, regardless of their school, 21 percent created something with AI. Among those who attended six or more, 56 percent did. The study needs to be repeated elsewhere, but it did not detect a difference between the two institutional groups on this measure. The design of the program, along with the amount of meaningful practice students receive, may matter even more.

Related: OPINION: Schools cannot teach AI literacy without a way to measure it

A useful question is whether particular combinations of instruction, practice, professional guidance and real-world opportunity produce meaningful results, and which students benefit. Answering that question will require universities to move beyond isolated pilots.

First, to evaluate their AI literacy programs, colleges should measure changes in students’ judgment, problem-solving, professional communication and ability to create useful work with AI. They should also track whether students gain access to internships or employment.

Second, universities should study programs across different types of institutions. Findings from any one program cannot automatically be assumed to generalize across different institutional contexts.

Third, employers should become partners in pilot program design rather than occasional guest speakers. They can help define real problems, review student work and explain which abilities matter on the job. Students need contact with professionals who can show them what responsible AI use looks like inside an actual organization.

Encouragingly, federal workforce policy is beginning to move in this direction. In July, the U.S. Department of Labor awarded nearly $162 million through five agreements to expand Registered Apprenticeship programs. The funding uses performance-based incentives tied to results such as the hiring of new apprentices, keeping them in programs and helping them advance.

Jobs for the Future, for example, a national nonprofit, received $40 million to support Registered Apprenticeship growth in roles building and maintaining the critical infrastructure that sustains the artificial intelligence, semiconductor and nuclear energy industries.

But apprenticeships are not university courses: They pay wages, provide federally recognized credentials and place learning inside a job. While colleges cannot simply copy that model, they can work toward the same goal: training that leads to demonstrated skills, meaningful employer participation and measurable outcomes.

Since generative AI reached college campuses, universities have shown that students are interested in learning how to use it. The next phase should determine which programs actually help them use AI responsibly and carry those skills into the workplace. Future grants should require shared measures, cross-campus comparisons and follow-up after students leave, since no single campus can build this evidence alone.

Without that evidence, AI workforce readiness will remain a collection of promising campus stories. With it, higher education can build a system that works for students no matter where they enroll.

Ngoc Cindy Pham is an associate professor of marketing at Brooklyn College, CUNY, and a visiting research professor at NYU Tandon. She is also a Fulbright Specialist and founder of BRIDGE AI Lab.

Contact the opinion editor at opinion@hechingerreport.org.

This story about college and AI was produced by The Hechinger Report, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for Hechinger’s weekly newsletter.

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