Generative AI through the Lens of Institutional Theory

This study examines the adoption of Generative AI (GenAI) systems through the lens of Institutional Theory. Using a mixed-methods approach, we analyze how coercive, normative, and mimetic pressures influence GenAI integration in organizations. Key findings reveal:(1) regulatory frameworks significantly shape GenAI adoption strategies, with variations across industries and regions;(2) organizations balance conformity to institutional norms with innovation, often through strategic decoupling;(3) GenAI’s unique capabilities challenge traditional institutional pressures, necessitating new governance models; and (4) early GenAI adopters emerge as new sources of mimetic pressure, accelerating industry-wide adoption. We propose a novel framework capturing the interplay between GenAI characteristics and institutional dynamics, contributing to both Institutional Theory and AI adoption literature.

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