Sensing without Seizing: The Institutional Barriers to AI Adoption in Indonesian MSMEs - Dadet Sugiarto; Eryco Muhdaliha; Jemmy Jemmy; Selamet Riyadi (Nomico, 2025)
Despite strong policy support, the adoption of Artificial Intelligence (AI) among Indonesian Micro, Small, and Medium Enterprises (MSMEs) remains critically low, creating a notable "digital paradox." This study investigates the "gap between sensing and seizing," defined as the disparity between awareness of AI opportunities and deployment capability. Integrating Dynamic Capabilities Theory and Institutional Theory, we examine how internal organizational capabilities intersect with contextual barriers. Utilizing an interpretivist approach based on the Gioia Methodology, data were analyzed from 28 MSMEs in the Special Region of Yogyakarta through indepth interviews, focus group discussions, and document analysis. The analysis reveals that while sensing capability is widespread, it relies heavily on informal peer networks and is constrained by a cognitive mismatch regarding the relevance of AI for small businesses. Seizing capability is hampered less by financial constraints than by weak absorptive capacity and challenges in assessing return on investment. Transforming capabilities among early adopters are incremental and highly dependent on external ecosystem support. The study concludes that this adoption gap reflects institutional voids, specifically infrastructure inequality and regulatory uncertainty, rather than a lack of entrepreneurial will. These findings refine the theoretical understanding of technology adoption in developing economies and offer strategic guidance for policymakers and technology providers.