Empowering Women through AI and the Gig Economy: Opportunities, Challenges, and Policy Implications

dc.contributor.authorHattab, Hala
dc.contributor.authorCharni, Hanen
dc.date.accessioned2026-06-26T20:10:20Z
dc.date.available2026-06-26T20:10:20Z
dc.date.issued2025
dc.description.abstractThe rise of artificial intelligence (AI) in gig economy platforms is changing employment as we know it. For many women, this shift brings a mix of opportunities yet pressing challenges. This research examines the relationship between AI-enabled gig work and women’s economic empowerment by conducting a systematic literature review (SLR) of 48 peer-reviewed studies published between 2010 and 2024. Using feminist political economy, this research investigates how technology and platform design sometimes interest with gender inequality. The review revealed five key themes: economic flexibility and empowerment, algorithmic bias, wage inequality, job instability, and digital marginalization. While gig platforms offer women a novel outlet for income and autonomy, especially for women facing limited access to formal jobs, many also reinforce pre-existing social and economic inequalities through algorithms, insecure working conditions, and technological exclusion. This research concludes with a call for gender-responsive policies and ethical platform design to enable women to utilize these platforms effectively as AI and gig-based economies are continuing to reshape the nature of work.
dc.identifier.citationHattab, Hala, and Hanen Charni. “Empowering Women through AI and the Gig Economy: Opportunities, Challenges, and Policy Implications.” 52nd EBES Conference, Istanbul, Turkey, July 3–5, 2025.
dc.identifier.urihttps://ebesweb.org/wp-content/uploads/2025/07/52nd-EBES-Conference-Program.pdf
dc.identifier.urihttps://repository.iou.edu.gm/handle/123456789/880
dc.language.isoen
dc.publisherEurasia Business and Economics Society (EBES)
dc.relation.ispartof52nd EBES Conference
dc.titleEmpowering Women through AI and the Gig Economy: Opportunities, Challenges, and Policy Implications
dc.typeConference Paper

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