The University of Wisconsin–Madison’s new College of Computing & Artificial Intelligence may be the system’s most visible and ambitious investment in the evolving field — but it is far from the only one.
Over the past handful of years, campuses across the Universities of Wisconsin have been developing ways for students to understand, responsibly use and navigate the evolving world of AI. From AI literacy to new academic majors, the approach varies, reflecting each university’s academic strengths and priorities.
As interest grows, so does the challenge of teaching a technology that is transforming industries, workplaces and higher education itself. Against the backdrop of a broader debate over how quickly AI is advancing — and what that means for society — universities are helping students apply the technology and recognize its limitations and possibilities.
Learning the basics
For some, that work begins with AI literacy. Emily Laird, an AI integration technologist at University of Wisconsin–Stout Polytechnic, sees investment in AI education as one way to address public uncertainty about the technology.
Laird specializes in AI literacy, working to integrate artificial intelligence into education, research and industry collaboration at Stout and across the state. Her work began a couple of years ago with trainings on ChatGPT. Since then, she has guest lectured at universities, launched a free podcast, Generative AI 101, about developments in the field, and started a weekly AI meetup on Stout’s campus.
“It’s never-ending,” she said. “This is not my job. It is literally my life. The team that I work with, we read system cards on weekends, we test models into the night. This is all we do. This is all we want to do.”
For Laird, preparing students for an AI-driven world starts with giving them a working understanding of the technology: what it can do, where it falls short and how to use it responsibly.
“I have a core belief that AI literacy is the new standard. Everyone should have access to it,” she said. “The more we can do to prepare future students and future workers, the better we will be as a state and beyond. Anything that is going to continue to advance access and knowledge around AI and computer science is a good thing.”
She recognizes it’s not an opinion everyone may agree with.
In recent months, artificial intelligence companies have come forward with instances of their technology acting in ways that appeared to evade instructions from humans. The events have raised questions from policymakers and communities alike over how the fast-growing technology can be developed safely as its usage becomes more widespread.
Laird contended that if students better understand AI, they’ll be more equipped to handle the implications of the technology. But defining what that literacy should look like remains a challenge. Laird said there is no consistent national framework for introducing students to generative AI, leaving colleges and universities to develop their own approaches.
That can create uneven levels of familiarity among students entering higher education, depending in part on whether their K-12 schools encouraged or restricted the use of AI.
“When students come into a higher education landscape from the K through 12 environment, we don’t know who has engaged with AI in the most effective ways or if this is their first time experiencing AI because it was really locked down,” she said. “That creates gaps. But that mirrors the industry.”
Industry applications
Professor Rahul Gomes helped create an AI major at UW–Eau Claire, which launched in fall 2025. The university has offered a certificate in the area since 2022.
That makes it one of the longest-running dedicated AI programs in the state.
Now, a year later, Gomes, an associate professor and chair of the Department of Computer Science, can point to the challenges a little bit easier.
While much of the initial interest in the major came from computer science students looking to understand an emerging technology, the rapid growth of generative AI has expanded course material.
The challenge is not simply teaching students what is happening in AI, but helping them understand how the technology can be applied, Gomes said. And that requires maintaining relationships with industry partners and learning how businesses are using AI.
Gomes and other faculty are also tasked with determining what employers need from graduates entering the workforce.
“It’s pretty exciting. We got into this field knowing it’s going to keep changing forever,” Gomes said. “What’s more important is not only teaching them what’s happening but also usability.”
Gomes said students have expressed concerns about whether AI will eliminate jobs or prevent them from learning if they use it too heavily. In response, the department is emphasizing more face-to-face instruction, ranging from by-hand quizzes, office hours and opportunities for students to work through questions with instructors.
“It’s important they know how to use this technology when they are asked to,” he said. “They need to know how to think without using AI — and then, you know this technology, so how are you going to use it?”
Gomes said he hopes to expand course offerings in generative AI and natural language processing, including through collaborations with other academic departments. He is also interested in strengthening community partnerships through opportunities such as internships and capstone projects.
Taking a ‘deep dive’
UW–Whitewater just launched its undergraduate major in AI this fall, a milestone Zach Oster has been building toward for years.
Oster, an associate professor and chair of the Department of Computer Science, said the department had long conducted AI research, and recent faculty hires brought additional expertise in artificial intelligence and machine learning. A few years ago, the university introduced an AI emphasis within its computer science major, creating a foundation for a more specialized program.
Then university leadership encouraged the department to consider taking the next step.
“Our chancellor came to us and said, ‘Have you thought about making it just an AI major?’” Oster recalled, noting at the time it would make Whitewater stand out to prospective students.
“We started looking to take a deep dive into how AI works, how to build custom AI models.… People don’t know us quite as much for computer science and AI, but this is a way to really highlight the great work that we do in that area.”
The university received approval from the UW System Board of Regents in December 2025, and the major welcomed its first students this fall.
Oster said the program reflects both the opportunities and the uncertainty surrounding AI.
Faculty members conduct research with undergraduate and graduate students, while the university’s Center for Ethical AI Integration examines how the technology can be incorporated into teaching across campus. The major also requires an ethics of artificial intelligence course developed by a university ethics specialist. The course is open to students beyond the major, too.
Whitewater’s goal mimics that of many across the state: to teach students to understand AI as a tool, not a replacement for their own thinking. That means balancing technical instruction with questions about how the technology should be used, Oster said. Students need to understand the foundations of AI and machine learning while also gaining experience with the tools and frameworks shaping the field.
“It’s a challenge to make sense of all of it, especially because it is changing every day,” Oster said. “That’s part of the job, staying on top of the latest changes and figuring out what’s going to be the long-term foundations that students need to know.”
He said faculty are working to build courses around foundational concepts that are unlikely to change quickly, while giving faculty flexibility to update the specific technologies and models covered in individual classes.
The department is also considering how much AI students should use in their coursework. In introductory classes, Oster said, students have fewer opportunities to rely on AI because they need to develop basic programming and problem-solving skills themselves. As they progress into their junior and senior years, they have more opportunities to use the technology where it makes sense.
“We want them to learn it — we don’t want the AI to learn it for them,” he said.
