Bridging the Gender Gap in AI Careers

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Artificial intelligence (AI) is rapidly reshaping global labour markets, yet the professionals designing, deploying, and governing these systems remain overwhelmingly male. This article examines the gender gap in AI careers through a feminist — specifically technofeminist and intersectional — lens, arguing that women's underrepresentation is not a pipeline problem alone but a structural, cultural, and technopolitical one. Drawing on recent workforce data, the article documents the scale of the gap across the AI career ladder, from entry-level hiring to the C-suite, and reviews four intervention areas: mentorship and role models, bias-aware recruitment, feminist-informed organisational policy, and inclusive AI education. To illustrate how such claims can be operationalised and tested empirically, the article presents a demonstration research design — including objectives, hypotheses, a fifty-respondent (N = 50) illustrative sample, descriptive means, and hypothesis-test results — that a future primary study could replicate with real data. The discussion connects each hypothesis back to its objective and result, and the article closes with policy recommendations and the limitations of both the literature and the illustrative model presented.