Women entrepreneurship in the age of AI and ESG: Micro- and macro-level drivers of adoption

Abstract

Artificial intelligence (AI) holds significant potential to advance women entrepreneurship and environmental, social, and governance (ESG) goals, yet adoption in emerging markets is constrained by both individual and institutional barriers. This study applies a two-panel Delphi method with 11 women entrepreneurs (Study 1) and 18 institutional experts (Study 2) to explore micro- and macro-level drivers of AI adoption. Across three rounds, participants rated competences, motivations, risks and institutional factors, with consensus assessed through Kendall's. Results show that women entrepreneurs view AI as a values-driven tool for sustainability but face challenges in skills, trust and resources, while institutional experts highlight regulatory frameworks, policy support and cultural norms as decisive enablers or barriers. The study contributes to Institutional Theory by integrating micro- and macro-level perspectives and offers practical insights for designing gender-sensitive policies and support mechanisms. Future research should extend these findings through longitudinal and cross-country analyses of women-led ESG ventures.