Women in STEM Program - Henry Luce Foundation

Through the Clare Boothe Luce Program for Women in STEM and STEM Convergence, we aspire to close the gender gap in the field, broaden the participation of women from diverse backgrounds, and advance women-led STEM innovation for positive social change.

Women, technology and AI: Five key takeaways for today’s world

To commemorate the International Day of Women and Girls in Science on 11 February, we spoke with Tamuna Kvintradze, Chief of Staff at Women in Tech Global. Ms. Kvintradze offered valuable insights into the barriers that women and girls encounter in STEM, highlighted the critical importance of their participation, and underscored the need to amplify their perspectives within mainstream and social media.

How AI Is Fueling the Gender Pay Gap in Tech

A new Wharton study finds that too few women are working with emerging tech, and that exclusion is driving a growing divide in pay.

Women in tech and AI in Europe: Can the region close its gender gap?

AI could be the turning point that finally unlocks women’s full participation in tech in Europe.

The Gender Gap in AI: Why We Need More Women in Artificial Intelligence - EIT Campus

Artificial intelligence is shaping our future, but who is shaping AI? In this blog, we explore the insights of Megi Mejdrechová, co-founder of RoboTwin, a…

Women in AI: Numbers Behind the Gender Gap in Tech

How is AI changing the game for women in 2026? From job shifts and personal life-hacks to the rise of female AI founders, explore the unique impact of women in tech today.

AI's Missing Link: The Gender Gap in the Talent Pool

Our analysis of data on nearly 1.6 million AI professionals worldwide reveals stark gender imbalances. Women comprise only 22% of AI talent globally, with even lower representation at senior levels – occupying less than 14% of senior executive roles in AI. Within the EU, the disparity is equally concerning.

Silicon Valley nonprofit encourages young women to lead in AI

A Bay Area gender gap in the tech industry threatens the full participation of women in the future of artificial intelligence.

The 'AI gender gap' narrative is missing the full picture | Fortune

New research shows women leaders are shaping AI strategy, ethics, and oversight—even as concerns about adoption gaps persist.

AI’s Gender Gap - Haas News | UC Berkeley Haas

Generative AI could boost productivity and reduce inequality, but women across the world are at risk of missing out.  A sweeping analysis by Nick Otis, PhD 25, Assistant Professor Solène Delecourt, and colleagues from Stanford and Harvard found that women were about 20% less likely than men to use tools such as ChatGPT, Claude, and […]

Women Are Avoiding AI. Will Their Careers Suffer? | Working Knowledge

Women are adopting generative AI technology at a significantly lower rate than men, in many cases because women question whether it's ethical to use the tools, according to research by Rembrand Koning and colleagues. If women are shying away from AI, could the gender gap in pay and job opportunities continue to widen?

Gender Productivity Paradox: Artificial Intelligence Is Failing Women - ICTworks

We're seeing decreasing distributive returns at higher AI exposure levels. Precisely when we should expect technology to be most equalizing.

From users to architects: Why girls must shape the future of AI

If girls aren’t shaping AI, we’re building a broken future. Empowering young women in tech is now a global necessity, not just a matter of fairness.

Report: Where are the women? Mapping the gender job gap in AI

As AI becomes ubiquitous in everyday life, closing the gender gap in the AI and data science workforce matters.

AI Development Needs More Women. Here’s What Leaders Can Do About It

Only 31% of professionals in AI development are women—learn how female talent can drive accountability, improve accuracy and improve AI's societal impact.

AI, gender bias and development

Generative AI is quietly reinforcing harmful gender stereotypes, shaping how we see the world and ourselves. How can we ensure it doesn't affect our development work in a biased way?