Digital public intelligence: Fuelling AI adoption across MSMEs in India

Digital public intelligence: Fuelling AI adoption across MSMEs in India

This study explores how Digital Public Infrastructure (DPI) influences Rogers' (1983) Diffusion of Innovation (DoI) theory adoption factors for Artificial Intelligence (AI) implementation among Indian Micro, Small, and Medium Enterprises (MSMEs). Despite their significant economic contribution (30% of GDP, employing over 110 million), MSME AI adoption lags behind larger enterprises. This research investigates how DPI affects the five key adoption factors—relative advantage, compatibility, complexity, trialability, and observability—in resource-constrained environments. A qualitative study of twenty participants led to the development of the Digital Public Intelligence (DPIQ) framework. Thematic and sentiment analysis of semi-structured interviews revealed how DPI influences each adoption factor, highlighting disparities between policy/industry perspectives and MSME operational realities, particularly within Bengaluru's technology ecosystem, while acknowledging broader geographical implications. This study makes three key contributions. First, it extends Rogers' framework by examining its application in resource-constrained environments, specifically how public infrastructure influences each factor. Second, it introduces the DPIQ framework, illustrating how DPI's layered architecture enhances adoption factors to facilitate AI implementation. Third, it provides empirical evidence of how adoption factors operate in emerging economies, emphasising the role of geographic location and resource constraints. These findings offer valuable insights for policymakers, MSME leaders, and researchers, which are crucial for bridging the gap between strategic vision and operational realities as emerging economies invest in DPI to accelerate technological advancement.