Generative Artificial Intelligence and Social Entrepreneurship: Rethinking Collaborative Ecosystem Innovation for Sustainable Development

ABSTRACT Generative artificial intelligence (GenAI) is increasingly conceptualised within social entrepreneurship as a socio‐technical resource embedded in collaborative ecosystems. Empirical and theoretical developments remain fragmented, particularly in explaining how ecosystem configurations shape socio‐technical innovation beyond isolated tool adoption. This study synthesises peer‐reviewed scholarship through a bibliometric–systematic literature review to map the intellectual structure and thematic evolution of the field. The following four research streams are identified: design and knowledge creation, stakeholder engagement, ethics and accountability, as well a sustainable entrepreneurship. Integrating institutional, governance, capability‐based and open innovation perspectives, the study develops an ecosystem‐level framework that articulates boundary conditions under which GenAI is associated with collaborative value creation. Three analytically derived mechanisms are specified for future empirical inquiry: algorithmic legitimacy, relational dynamic capabilities and distributed sustainability capability. The review highlights enduring gaps, including limited treatment of participatory oversight, power asymmetries and digitally marginalised contexts. By advancing a theoretically integrated and mechanism‐oriented account, the study contributes to cumulative research on GenAI‐enabled social innovation and provides a structured basis for context‐sensitive governance deliberation.