As companies seek ways to apply AI effectively and responsibly, researchers, faculty, and students at the University of California are contributing knowledge in new areas.
Artificial intelligence has gone from being the stuff of science fiction to being part of everyday life. It searches online, summarizes email inboxes, writes code, guides robots in factories, helps diagnoses in hospitals, and shapes conversations in nearly every boardroom. Technology is coming quickly and public perception is still forming.
For many organizations, the question is no longer whether AI matters, but how to apply it effectively and responsibly. Increasingly, they are looking to UW-Madison experts for guidance.
That expertise extends across the University. Faculty and researchers at schools and universities are approaching AI from a variety of angles, from business and engineering to healthcare and public systems. For example, the university’s AI for Business Hub includes 23 CEOs, vice presidents, and board members from Fortune 500 companies, including Google, Walmart, Reddit, Medtronic, Kimberly-Clark, Bain, and Accenture. The School of Computer, Data, and Information Sciences (CDIS) is also evolving into the School of Computing and Artificial Intelligence at this time, reflecting the growing importance of the field.
We work directly with companies in Wisconsin to explore how artificial intelligence can solve real-world problems. They improve tools for major health systems, streamline aerospace supply chains, and build the AI literacy skills that employers increasingly expect.
To better understand how these partnerships are forming across campus, we spoke to UC Madison leaders who work at the intersection of research, education, and business activities.
Learning by doing: Where students and industry meet
Justin Hines — Director of Corporate Relations, CDIS
Q: How does CDIS support collaboration between industry and campus around AI, particularly through education, research, and applied projects?
A: Many organizations, from startups to large enterprises, have yet to decide where and how AI will create value in their operations. Capstone teams enable companies to consider these questions in a low-risk, high-impact environment. Students will help vet ideas, find solutions, and identify technical challenges early to reduce risk in AI deployments before production or widespread implementation. This model benefits both students and partners by aligning academic learning with real-world business needs.
Q: What AI-related questions or challenges are companies currently most interested in working with UW-Madison to consider?
A: Most companies are focused on practical, short-term issues and how existing AI tools can be integrated into their organizations to have measurable impact. Organizations are much more interested in asking how AI fits into their specific industry, culture, and operational constraints.
Matt Seitz — Executive Director, AI Hub for Business
Q: From your perspective, how are industry partners currently thinking about AI, and what types of applications and capabilities are they most interested in exploring or adopting?
A: Most business leaders I talk to have come off the sidelines and are now taking action on AI. While this theory is interesting, they are looking for practical ways in which AI can increase value for companies. While many companies are starting with customer chatbots and process automation for efficiency, the most advanced companies are using AI to build software and capture strategic growth. First movers have a real competitive advantage. In April, we will host the AI for Business Ground Truth Summit to help leaders move from theory to action.
Q: What are the most important AI skills and mindsets you want university students to have now after they graduate?
A: The leaders of the future will not be the most effective users of AI, but the ones who use it most effectively. Students need to develop judgment about where AI can add value and where human oversight is essential. For example, a student might use AI to create a competitive analysis and use completely fabricated market size data to obtain sophisticated and confident results. The skill is not producing any output. It’s about knowing how and when to validate it before it hits the VP’s desk. This means you can fully understand the technology, ask the right questions, identify limitations, and make informed decisions about how to use and deploy AI within your organization.
Q: Fast forward five or 10 years, what is one way that AI could change the way people in Wisconsin work and do business that might surprise them today?
A: In five years, AI will be embedded in every job, just as today’s workers use Excel and Google. Tasks that previously took days, such as financial modeling, market analysis, and competitive landscape construction, now take hours with AI support. And it’s not just knowledge work. Factory managers can use AI to predict equipment failures, sales teams can walk into meetings with AI-generated insights, and supply chain leaders can reroute logistics in real-time. The value of human workers will shift to judgment, creativity, and relationship building. Today, companies that invest in building human and AI capabilities will be able to compete with organizations twice their size.
Transform real-world problems into AI solutions
Kyle Cranmer — Director, University of California, Madison Data Science Institute
Q: What industry-driven questions and challenges do you see most frequently in the AI and data science space today?
A: The content varies widely, but the common theme is how to deeply integrate AI and data science into business processes. This includes incorporating large-scale language models and agentic AI approaches, and rethinking how data is managed to take full advantage of recent advances.
Closely related are the challenges of trust, such as dealing with hallucinations, maintaining privacy and confidentiality, and handling sensitive information responsibly.
Q: How does the Data Science Institute help connect AI research, education, and real-world problem solving from UW-Madison to UW-Madison, especially when collaborating with industry partners?
A: Most real-world problems require a period of transformation before an AI approach can be realized. The Data Science Institute brings together affiliated faculty with deep domain expertise and translation experience. This allows us to engage the right AI researchers across campus, whether the problem originates with academic research or industry partners.
Q: How will AI accelerate discovery in areas important to Wisconsin residents and Wisconsin industry?
A: AI is dramatically accelerating the pace of discovery, especially in areas such as drug discovery. AI is leading the search for new materials with unique properties, such as the ability to sequester CO2 from the atmosphere. Although these drug candidates and materials still require validation through traditional laboratory methods, AI is transforming the front end of the discovery process.
John Garnetty — Managing Director of Business Engagement
Q: Why do companies choose to work with the University of Wisconsin-Madison instead of trying to solve AI problems themselves?
A: I think both are true. There are areas of research related to AI where we excel, and that also applies to the wider university, but there are also other, often complementary, areas of research where industry excels. Through sustained collaboration, we can make the most of our respective strengths and do more together than separately. But to directly answer your question, companies specifically choose to partner with UW-Madison. Because we have deep expertise in AI and data science, and incredible breadth as an institution. Few universities have world-class researchers in medicine, education, engineering, agriculture, and business. More succinctly, the nature of most private sector work is cross-sectoral, and the strong interdisciplinary research environment at the University of Wisconsin-Madison reflects that.
Q: How will these AI partnerships support Wisconsin’s economic development and workforce goals?
A: I think these partnerships and their outcomes are absolutely critical to the state’s economic development and workforce goals. I agree that AI is a revolutionary technology on a par with the internet, and that there are few, if any, aspects of our society that will not be affected by AI. As the state’s flagship university, we feel there is much we can do to lead the state in this area, through partnerships not only with industry, but also with government and community organizations, as well as with our peer institutions of higher education who are doing great work in this area.
