By Dr. Alexandra Urban, Learning Science Research Lead, Coursera

As we mark International Women’s Day, I am delighted to present a fresh Coursera playbook, which investigates practical approaches for bridging the existing gender disparity in Generative AI (GenAI) capabilities by identifying methods to enable more women to leverage GenAI.

Despite the growing significance of GenAI in workplaces globally, women account for merely 32% of enrollments in this area on Coursera, which risks perpetuating existing inequalities in the advancement and utilization of technology. Addressing this disparity is vital to foster a more inclusive future and a fairer workforce.

Our Closing the Gender Gap in GenAI Skills playbook delineates key obstacles that deter women from enrolling in GenAI courses, such as:

• Restricted time and ambiguous guidelines impede skill acquisition – Numerous women cite “lack of time” as their primary reason for abandoning STEM courses, illustrating the common challenge of managing caregiving and work duties. Furthermore, uncertainty regarding how AI and GenAI integrate into careers can cause reluctance. On Coursera, flexible learning structures and AI-assisted coaching are proving successful in mitigating these barriers.
• Perceived lack of relevance – Just 36% of women perceive that GenAI can propel their careers, compared to 45% of men. This perception divide hampers upskilling efforts. Women are more inclined to participate when GenAI’s relevance is contextualized through practical examples in sectors like healthcare, education, and everyday tasks. Real-world case studies and interdisciplinary GenAI programs have demonstrated their effectiveness in enhancing engagement and completion rates.
• Lack of confidence diminishes persistence – Self-efficacy is crucial for successful learning outcomes. Women frequently hesitate to engage in GenAI courses due to a lack of confidence, even when they possess the required skills. On Coursera, women are six times likelier to enroll in introductory GenAI courses than those at intermediate levels, indicating a preference for structured, accessible entry points.

Interventions that offer tailored learning support, well-defined milestones, and mentorship opportunities have been shown to enhance persistence and completion rates among female learners.

The playbook also emphasizes countries where the gender disparity in GenAI training is least and most pronounced. We find that:

• The gap is minimal in emerging markets across Europe and Latin America. Uzbekistan has achieved the most equitable participation in GenAI training: there, female learners constitute 49.7% of total GenAI enrollments. Ecuador (47.7% female learners), Czech Republic (44.9%), and Colombia (41.8%) also exceed female enrollment rates of 40% within our GenAI offerings.
• The gap is greatest in Middle Eastern and Asian markets. Pakistan showcases the world’s most significant GenAI enrollment gap on Coursera, with women accounting for just 15.9% of the nation’s GenAI learner population. Egypt (22.2% female enrollments), Israel (23.4%), and the United Arab Emirates (23.8%) rank among the nations with the most substantial GenAI gender disparities. 

Merve Hickok, President & Policy Director, Center for AI and Digital Policy and Lecturer, University of Michigan, stated: “While it’s uplifting to witness so many individuals adopting GenAI skills, we must address the gender gap in this domain. We require diverse perspectives to shape the development, implementation, and ethical use of these machine learning systems. Organizations need to ensure that women are represented in decision-making processes regarding these powerful technologies.” 

We trust that this playbook delivers data-driven methods for educators, businesses, and governments to promote enhanced inclusivity in GenAI learning. By crafting equitable learning environments, we can guarantee that all women – regardless of their background, experience, or location – can upskill, persist, and flourish in the GenAI economy.

You can access our Closing the Gender Gap in GenAI Skills playbook here. 

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