Minimum Viable Governance for Generative AI
Name
2026_0301_GenAIGovernance_VanderMeulenJewerLevallet.pdf
Size
318.61 KB
Format
Adobe PDF
Checksum (MD5)
8f126cbdcebb5e459ab372fa5ca646b4
Author(s)
van der Meulen, Nick
Jewer, Jennifer
Levallet, Nadège
Date Issued
March 19, 2026
Publisher
Cambridge, Mass.: Center for Information Systems Research, Sloan School of Management, Massachusetts Institute of Technology
Citation
Van der Meulen, Nick, Jennifer Jewer, and Nadège Levallet. “Minimum Viable Governance for Generative AI.” MIT CISR Research Briefing Volume XXVI, no. 3 (March 2026). https://dspace.mit.edu/handle/1721.1/174985.
Series/Report no.
MIT CISR Research Briefing, Vol. XXVI, No. 3
Abstract
Traditional technology governance assumes stable technologies, predictable consequences, and manageable demand. Generative AI (GenAI) upends these assumptions: its pace of adoption outstrips centralized review capacity, while the technology itself transforms faster than conventional governance mechanisms can adapt. This briefing introduces minimum viable governance, a framework designed to match the pace of GenAI while enabling the organization to sense and seize opportunities. Drawing on an in-depth case study and prior MIT CISR research, we identify four characteristics of minimum viable governance that leaders can apply across governance domains.
Subjects
Assessing Performance and Value
IT-Related Business Risk
Decision rights/governance
Information Technologies
Data, AI, and Analytics
Terms of Use
CC BY-NC 4.0 (Attribution-NonCommercial 4.0 International)
Persistent DSpace Link
