<![CDATA[Artificial intelligence (AI) is increasingly recognized as a potential driver of productivity, innovation, and economic transformation. However, the economic benefits of AI adoption are not necessarily distributed equally across individuals, enterprises, and communities. In emerging economies, technological adoption occurs within social environments characterized by uneven digital capabilities, diverse cultural practices, and varying levels of institutional trust. This article develops a qualitative research framework to examine how local knowledge and institutional trust shape the pathways through which AI contributes to inclusive economic development. Drawing on the capability approach, institutional theory, and sociotechnical perspectives, the study conceptualizes AI not merely as a technological resource but as a socially embedded capability whose developmental outcomes depend on local interpretation, institutional legitimacy, and opportunities for meaningful participation. The proposed research employs an interpretive qualitative multiple-case study design, with small enterprises, community-based economic organizations, and local institutions in Indonesia as potential empirical settings. Data will be collected through semi-structured interviews, observations, and document analysis, followed by reflexive thematic analysis. The study aims to develop a context-sensitive theoretical explanation of how AI-enabled economic opportunities are translated or fail to be translated into broader participation, improved economic agency, and more equitable access to economic benefits. By integrating local knowledge and institutional trust into the analysis of AI-enabled development, the article seeks to contribute to debates on inclusive digital transformation in emerging economies.]]>
