Artificial Intelligence, Gender, and the Technological Conversion Gap: A Research and Policy Agenda

Abstract

The global expansion of artificial intelligence is reshaping organizations, labor markets, and innovation ecosystems at an unprecedented pace. Yet the governance of this transformation remains deeply gendered: women are systematically underrepresented in AI research, excluded from technology leadership pipelines, and marginalized in the venture capital flows that fund AI innovation. This paper theorizes this disconnect, situates it within a multi-level analytical framework, and derives from it a structured research and policy agenda. It argues that these disparities are not incidental but structural, reflecting what it terms the Gender Technological Conversion Gap (GTCG), a systemic disconnect between women's accumulated educational and scientific capital and their effective participation in technological leadership and AI governance. Drawing on a framework organized around three levels (knowledge production, organizational systems, and innovation dynamics) and on global data together with Tunisia as an illustrative case, the paper derives four priority research agendas for management science and a corresponding agenda for decision-makers. Its central contribution is to name this disconnect as a measurable conversion rate that institutions can estimate, compare across contexts, and track over time, rather than a diffuse problem of representation. This article is the extended, written version of the inaugural keynote presented at the International Conference on Gender Studies (ICGC 2026), Gammarth, Tunisia, June 2026.