On International Women's Day, New Coursera Report Reveals Global Progress Towards Narrowing GenAI Gender Gap

New Coursera report shows year-over-year increase in women seeking to gain GenAI skills

• Female share of GenAI enrollments on Coursera rises from 32% to 36% year-over-year
• Among Enterprise learners, female enrollment share rises from 36% to 42%
• Gender gap in GenAI learning widens in the US, Canada, UK; narrows in India and Latin America

As the world prepares to celebrate International Women's Day, new data released today by Coursera (NYSE:COUR), a leading global online learning platform, highlights the progress being made to improve female access to key skills, including GenAI and Critical Thinking. Between 2024 and 2025, the female share of enrollments in Coursera's 1,100+ GenAI courses rose from 32% to 36%.

One Year Later: The Gender Gap in GenAI builds on Coursera's original Gender Gap in GenAI report, examining whether, and how, institutions are successfully narrowing gender gaps in the skill areas that will define tomorrow's economy. It finds that women's engagement with the technology is accelerating faster than that of their male peers.

"Research shows that GenAI will accelerate the global economy and transform work, with some estimates suggesting it could increase the world's wealth by as much as USD$22.3 trillion by 2030," said Dr. Alexandra Urban, report author and Learning Science Research Lead, Coursera. "If economic gains are to be shared equitably, institutions must equip people with the skills to use emerging technologies. When barriers are lowered and GenAI skills feel practical and attainable, women are eager to adopt them at scale."

Though the global gap is narrowing, there are significant regional and local differences in uptake of GenAI skills by gender. Key regional trends include:

• Latin American nations have recorded a doubling in its share of GenAI enrollments on Coursera from female learners year-over-year (YoY). Standouts include Peru (+14.5 percentage points YoY), Mexico (+5.3 percentage points), and Colombia (+4.5 percentage points).
• Asia Pacific nations have also consistently narrowed GenAI gender gaps on Coursera. Uzbekistan is a global standout, with an 8.8 percentage point increase in their share of enrollments from female learners.
  • India, Coursera's biggest market for GenAI enrollments globally, has recorded a 2.2 percentage point increase, while Vietnam, Indonesia, Thailand, and the Philippines have also increased their share of female enrollments in GenAI courses YoY.
• However, in many of the Anglophone and economically developed countries, men's enrollments are growing faster.
  • In the United States (-0.9 percentage points), Canada (-1.0 percentage point), the United Kingdom (-1.8 percentage points), Spain (-1.1 percentage points), and Germany (-0.2% percentage points), women represent a smaller share of total GenAI enrollments in 2025 than 2024.

Once the enrollment barrier is cleared, female learners often demonstrate higher levels of persistence in GenAI learning. Coursera finds that:

• Across a meaningful minority of countries, women are more likely than men to complete GenAI courses once they enroll, demonstrating strong persistence and commitment to these pressing new skills.
• Across the top five countries for GenAI enrollments, women are 1.5 times more likely to complete GenAI courses than their male counterparts, once enrolled.
• These patterns suggest that the primary barrier for women in GenAI is often entry, not capability or motivation, especially in Latin America, Asia Pacific, and the Middle East. Once engaged, women frequently persist at equal or higher rates than men, reinforcing the importance of removing initial barriers to participation.

Coursera's platform data indicates that courses which frame GenAI as an immediately useful tool for productivity and problem-solving receive higher shares of enrollments from female learners. Examples include:

• Generative AI Content Creation from Adobe (49% female enrollments)
• AI in Education: Leveraging ChatGPT for Teaching from Wharton & OpenAI (48.8% female enrollments)
• Excel and Copilot Fundamentals from Microsoft (45.2% female enrollments)

The report also offers recommendations for institutions seeking to accelerate progress towards equitable access to skills. These include:

• Design GenAI courses for beginners that feature real-world applications.
• Ensure visible representation and inclusive pedagogy across educational modalities.
• Expand access through policy, partnerships, and localization.
• Reinforce participation through social validation and diverse role models.
• Pair GenAI skills with durable human capabilities like critical thinking.

To learn more, download the One Year Later: The Gender Gap in GenAI report here.

About Coursera

Coursera was launched in 2012 by Andrew Ng and Daphne Koller with a mission to provide universal access to world-class learning. Today, it is one of the largest online learning platforms in the world, with 197 million registered learners as of December 31, 2025. Coursera partners with 375+ leading university and industry partners to offer a broad catalog of content and credentials, including courses, Specializations, Professional Certificates, and degrees. Coursera's platform innovations — including generative AI-powered features like Coach, Role Play, and Course Builder, and role-based solutions like Skills Tracks — enable instructors, partners, and companies to deliver scalable, personalized, and verified learning. Institutions worldwide rely on Coursera to upskill and reskill their employees, students, and citizens in high-demand fields such as GenAI, data science, technology, and business, while learners globally turn to Coursera to master the skills they need to advance their careers. Coursera is a Delaware public benefit corporation and a B Corp.

Methodology

This analysis draws on de-identified, platform-level Coursera learner data globally, comparing year-over-year GenAI enrollments and completions from 2024 to 2025 across both consumer and enterprise learners. Learner gender was based primarily on self-reported profile information; where unavailable, gender was inferred from first names when possible. Records with unknown or non-binary gender were excluded from gender-share calculations. Enrollment counts and completion rates were calculated at scale, with completion defined as the number of learners who finished all graded assessments divided by the total number who enrolled. To ensure stability and reliability of results, course-level analyses were limited to offerings with adequate sample sizes (e.g., more than 3,000 enrollments per gender), and country-level analyses were restricted to geographies with sufficient enrollment volumes.

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For media: Arunav Sinha, [email protected]