Today’s science, technology, engineering, and math (STEM) students will be entering the workforce at a pivotal moment. They grew up on iPads, attended high school classes on Zoom during the COVID pandemic, and are navigating college amid an AI revolution. Now, with generative and agentic tools able to accelerate many tasks, a burning question remains: How can universities adapt to this new era and help students harness AI’s advantages without weakening the foundational knowledge and judgment they will need as engineers?

Academic institutions are working to help students get the most out of AI tools while ensuring the next generation of engineers doesn’t cut corners on foundational knowledge. One trend is universities placing greater emphasis on critical-thinking tasks so students don’t swallow GenAI slop in totality. Just as large language models need guardrails, universities are developing tests and quizzes to ensure students learn properly and to minimize cheating. [See Table of University Approaches below.]

“We are seeing people who skate through or miss something fundamental that was important for a particular job, and they have to go back and relearn it,” said Alexandra Werth, assistant professor in biomedical engineering at Cornell University. “Higher ed is in trouble if we don’t work hard to make sure that doesn’t happen. I just went to an American Society of Engineering Education conference, where there were thousands of engineering educators, and this was what everyone wanted to talk about and figure out because this is what makes education relevant. People are trying a lot of different things, and we’re still in a weird place where AI technology is constantly changing.

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