At UW–Madison, many of the most important breakthroughs have not come from any single discipline, but from intentional collaboration across fields. Solving complex challenges requires more than expertise. It requires creating the right structures to bring people together and make collaboration part of everyday work.
That idea helped shape the Wisconsin Energy Institute (WEI), which opened in 2013 as the “front door” for energy research on campus. At the time, more than 90 faculty members were working on energy-related questions across campus, spread across 24 buildings. Their goals often overlapped, but physical distance and traditional academic structures made collaboration less natural.
Bringing those researchers together under one roof was a deliberate choice. WEI was designed to encourage interaction, speed up the exchange of ideas, and support work that spans disciplines. The building itself plays a role in that mission, with its location and shared spaces making connection part of the daily routine. Researchers collaborate across fields, work closely with industry partners, and engage with the public to advance clean energy solutions more effectively.
More than a decade later, WEI has demonstrated the value of this model. By reducing fragmentation and fostering sustained collaboration, it has helped accelerate innovation and position UW–Madison as a leader in energy research.
Now, the UW is applying that same philosophy to artificial intelligence (AI). Unlike energy research in 2013, AI does not center on a single institute. Instead, the university is applying hub-building principles across a coordinated set of efforts.
Like energy, AI is not confined to a single discipline. AI work is already happening across campus, with expertise distributed across departments but with fewer formal structures connecting it.
To bring that work into a more connected ecosystem, UW–Madison is coordinating AI hubs and initiatives that link research, education, and industry engagement. The goal is to strengthen collaboration across fields and translate research into real-world applications more effectively.
One example is the UW–Madison Tech Exploration Lab, which serves as an applied launchpad for emerging technologies like AI. The lab brings together students from across campus to work on real industry challenges, experiment with new tools, and develop practical applications in a collaborative environment. At the same time, broader campuswide initiatives are reinforcing AI as a strategic priority and investing in the infrastructure needed to support interdisciplinary work at scale.
Just as WEI brought together energy researchers who were previously working in isolation, UW–Madison’s AI efforts are focused on better connecting work that already exists and accelerating it through shared momentum across disciplines.
