It’s 2026. Artificial intelligence is well ingrained into the business world. But things are moving fast and government officials, both locally and nationally, are reckoning with how to implement rules and regulations.
For the general public, it’s hard to keep track of the rapidly changing environment and what decisions are being made. And, when decisions are being made in the dark, you can’t advocate for your position or hold your lawmakers accountable.
Stefani Langehennig, an assistant professor of the practice at the Daniels College of Business, is trying to change that with her research, shining more light on AI policy changes to ensure accountability. Langehennig is approaching this from a distinctive angle. She’s a trained political scientist, now working in the Daniels Department of Business Analytics.
Her admittedly nonlinear career path wove through public policy consulting firms in the U.K. and U.S., arming her with a unique perspective.
“I was dealing with big public contracts for the U.K. and the European Union (EU), leading a brand-new data science team at this consulting firm,” she said. “We were focusing on the data analytics side of public policy and evaluation, and the numbers that come to bear to those problems.”
She’s continued that melded interest in data and policy at Daniels, now turning her focus to AI regulation.
“I really want to understand how AI policy is evolving, who’s the first mover, what’s impacting how states approach this and what the transparency mechanisms are around AI governance,” she said.
To do this, she’s using grant funding from the American Political Science Association to help build a dashboard that tracks the legislation states are imposing on AI. It will be hosted on a public facing site and housed at the Daniels Center for Analytics and Innovation with Data (CAID). Langehennig expects to hire a graduate student worker to help build it and wants to share their findings with the rest of the country.
“We’ll have it be a public-facing resource that academics, practitioners, students or whoever can use,” she said. “My hope is that we can also do some reporting around it as well. I don’t want it to just be this kind of data tool that people can only go poke around on. I want to actually deliver some insights and takeaways.”
In addition to the dashboard, Langehennig is also focused on how frequently lawmakers are using evidence-based policies and what the balance is around transparency and trust.
“I’m trying to understand how these transparency tools empower people to have some oversight or an accountability mechanism for lawmakers, but also how that may backfire, erode trust or slow down the lawmaking process,” she said.
The AI avalanche is lot to manage for businesses and lawmakers alike, but Langehennig preaches slower, more measured decision making around policy.
She points to the EU AI Act as an example of quickly implemented policy that needed more time. Now, less than two years after it was unveiled, the EU’s sweeping policy is being reformed. She doesn’t want the same to happen in the U.S.
“We need slower, incremental change that’s actually documenting what’s happening when states pass this legislation to understand what we need to do next,” she said.