Organizational sensemaking and AI adoption in U.S. local governments

Artificial intelligence (AI) is rapidly entering public administration, yet adoption across U.S. local governments remains uneven. Existing explanations emphasize structural capacity, expecting internal barriers to constrain adoption. Drawing on Weick’s sensemaking perspective as an interpretive lens, this study examines AI adoption as shaped by how organizations interpret technological opportunity and enact deliberate responses. Using the 2024 ICMA Artificial Intelligence Survey, this study tests whether internal barriers, AI potential, and organizational initiative explain variation in adoption. Findings show that internal barriers are not significantly associated with adoption, whereas AI potential and organizational initiative are positively associated with it. These findings suggest that in equivocal technological contexts, structural conditions operate through interpretive processes, and that what organizations possess shapes adoption through how they make sense of emerging technologies and mobilize action. This study demonstrates the analytical value of sensemaking as a framework for understanding public sector responses to technological change.