— By Buckley Brinkman, advisor to the Wisconsin Center for Manufacturing and Productivity
For WisBusiness.com
The more I travel around Wisconsin, the more frustrated I become with how we approach shared opportunities — especially around Artificial Intelligence.
Our independence is one of our strengths; but our provincialism often keeps us from aligning around big opportunities. If we want to lead in AI, we must pivot some of our infrastructure to enable real intrastate collaboration and healthy “coopetition.” We need to approach AI — Wisconsinbly.
Wisconsinites lean toward action. That’s usually a strength. We get things done while others are still studying the issue. That won’t work with AI because it moves fast and touches everything. If everyone charges ahead independently, we risk fragmentation, duplication, and missing opportunities.
Many of our AI leaders share this bias for action. They are building solutions — a good thing – but too few are stepping back to ask how we create collective advantage. Individual progress is happening. Coordinated impact is not. It’s easier to build your own solution than to align around a bigger picture. I understand that instinct. Still, we can do better.
The good news is we already have statewide platforms that could help us align. The Universities of Wisconsin, the Wisconsin Technical College System, the statewide Chamber network, the Wisconsin Economic Development Corporation, and the Wisconsin MEP Network all operate across regions and serve defined stakeholders. Each runs valuable initiatives. They operate independently and have difficulty aligning.
Historically, Wisconsin struggles to create consistent statewide approaches to major opportunities. When we fail to align, we dilute our impact — and other states move ahead. We need a Wisconsinble approach to AI that uses our resources more intentionally to address our biggest challenges and capture this opportunity.
My vantage point in manufacturing allows me to participate in many AI conversations. Recently, I engaged with leaders from the UW Regents, the Northwestern Mutual Digital Science Initiative, higher education campuses across the state, and entrepreneurs building AI-enabled companies. Vibrant conversations with smart people, around important initiatives, creating real momentum.
Unfortunately, they largely happen in parallel.
In the past, parallel experimentation often worked well for Wisconsin. For example, take Industry 4.0 with its advanced manufacturing technologies like additive manufacturing, augmented and virtual reality, and connected devices. Implementation was expensive, complex, and risky. That slowed adoption and gave us time to coordinate informally as we learned.
AI is different.
In some applications, AI is cheaper and easier to deploy. In others, it is more complex and riskier. In every case, its speed and scope outpace our traditional, loosely connected approach. The breadth of AI’s impact demands a new level of collaboration and learning if we want to maximize opportunity and manage risk.
Right now, AI activity across Wisconsin resembles scattered tiles: Interesting experiments, emerging regional specialties, and diverse use-case libraries. These are essential building blocks.
What’s missing is the mosaic.
Creating that mosaic — Wisconsinbly — requires collaboration and strategic intent beyond our normal comfort zone. We need stronger connections between regions that build on emerging specialties to create shared learning loops that accelerate implementation while reducing duplication and risk. When we do this well, we expand our collective capability, generating more impact and creating durable advantage.
Wisconsin can lead in AI implementation — particularly in manufacturing. This leadership will not happen organically. It must be designed.
We should create a Wisconsin AI Network – strong local nodes connected through deliberate statewide mechanisms. Local nodes would address community needs and develop specialized talent. The statewide network would facilitate collaboration, share use cases, align investments, and accelerate learning and safe implementation. Done right, this approach allows us to move farther, faster, and more responsibly.
There is much to learn. There is much to build. All of us have a role to play.
When we attack this opportunity Wisconsinbly, we won’t just participate in the AI era — we will lead it.
