Stefani Langehennig, PhD

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Research Area

AI and to legislative and policy analysis to identify regulatory trends, policy risk, and government regulation.

Industry Impact

• Researches how machine learning and natural language processing can be applied to legislative and policy analysis to identify regulatory trends, policy risk, and government priorities.
• Develops tools that help organizations monitor evolving technology and AI regulations, supporting strategic planning, compliance, and operational decision-making in rapidly changing policy environments.

Biography at a Glance

Stefani Langehennig is an Assistant Professor of the Practice in the Business Information and Analytics Department at the University of Denver’s Daniels College of Business. She is also the lead director for the Center for Analytics and Innovation with Data (CAID) and helps lead the MSBA Capstone Program at DU. She teaches courses on Python programming, AI in analytics, big data management platforms, frequentist statistics and project management.

Her research sits at the intersection of data science, public policy and legislative institutions, with a focus on how computational methods can be used to evaluate policymaking and government transparency. Her current work examines how AI is reshaping policymaking and governance, particularly through new forms of data transparency and civic monitoring often described as “monitory democracy.” She combines machine learning, large language models and computational text analysis with traditional qualitative and quantitative approaches to study legislative behavior, policy design and evidence-based governance. She also collaborates with industry and public sector partners on applied analytics projects related to AI governance, policy evaluation and data-driven decision-making.

Prior to joining the University of Denver, she worked as a lead data scientist and managing consultant at ICF, where she led public sector analytics projects in the United States and United Kingdom. She earned her PhD in political science from the University of Colorado Boulder.

Education

• PhD in Political Science and Quantitative Methods, University of Colorado Boulder, 2019
• MA in Political Science and Quantitative Methods, University of Colorado Boulder, 2016
• MS in Political Science, University of Nebraska Omaha, 2014
• BA in Government, University of Texas at Austin, 2009

Recent Publications

• CAID Launches U.S. State AI Policy Tracker: https://du-caid.github.io/reports/ai-tracker-launch.html
• Colorado’s AI Law Pause: What It Means for People Working in Data Science: https://realworlddatascience.net/the-pulse/posts/2026/02/02/colorado-AI.html
• Colorado is pumping the brakes on first-of-its-kind AI regulation to find a practical path forward: https://theconversation.com/colorado-is-pumping-the-brakes-on-first-of-its-kind-ai-regulation-to-find-a-practical-path-forward-269065
• The Politics of AI Innovation in the U.S. States (Sema Technologies): https://www.techpolicy.press/the-politics-of-ai-innovation-in-the-us-states/

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