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AI Gender Gap Exposed: How It Impacts Legal Tech Innovation

AI Gender Gap Exposed: How It Impacts Legal Tech Innovation

Key Points

- Research suggests the AI workforce globally is around 300,000, with women at 22% (about 66,000) and men at 78% (about 234,000).

- It seems likely that AI academia has about 10,000 faculty positions, with women at 16% (around 1,600) and men at 84% (around 8,400).

- The evidence leans toward a significant gender gap in both sectors, with men outnumbering women substantially.

AI Workforce

The AI field, encompassing professionals in machine learning, natural language processing, and more, has an estimated global workforce of 300,000. Research indicates women make up about 22%, translating to roughly 66,000 individuals, while men account for 78%, or about 234,000. This distribution, consistent with findings from Deloitte ([Deloitte US](https://www2.deloitte.com/us/en/pages/consulting/articles/state-of-women-in-ai-today.html)) and Forbes ([Forbes](https://www.forbes.com/sites/falonfatemi/2020/02/17/bridging-the-gender-gap-in-ai/)), highlights a notable gender disparity.

AI Academia

In academia, the number of AI faculty positions globally is estimated at around 10,000, based on analyses like the Stanford AI Index Report ([Stanford AI Index Report 2021](https://aiindex.stanford.edu/ai-index-report-2021/)) and surveys from the Computing Research Association ([Computing Research Association](https://cra.org/resources/cra-taulbee-survey/)). It seems likely that women hold about 16% of these positions, or approximately 1,600, with men occupying 84%, or about 8,400. This figure aligns with data showing women making up 18% of AI PhD recipients in North America and 16% of tenure-track faculty in AI-focused roles, per the Stanford report.

Gender Gap

The gender gap is evident, with men significantly outnumbering women in both industry and academia. This disparity, while not new, underscores the need for inclusive strategies to balance representation, especially given AI's growing societal impact.

An unexpected detail is the variation in regional representation, such as Eastern Europe (e.g., Latvia) showing nearly 50% female AI professionals, contrasting with global averages, as noted in some reports ([Forbes](https://www.forbes.com/sites/falonfatemi/2020/02/17/bridging-the-gender-gap-in-ai/)).

Addressing the Gender Gap in AI: Workforce and Academia Insights Introduction

Artificial Intelligence (AI) is transforming industries and academia, yet it faces a persistent challenge: a significant gender gap. At Karta Legal, our focus on legal tech consultancy extends to understanding how diversity impacts AI development, especially given its implications for fairness and equity in technology outputs. This article explores the current representation of women versus men in the AI field, both in the workforce and academia, and examines the extent of the gender gap, drawing on recent data and reports as of March 2025.

AI Workforce: Numbers and Distribution

Research suggests the global AI workforce comprises approximately 300,000 professionals, a figure derived from various industry reports and estimates, such as those from LinkedIn and the World Economic Forum ([World Economic Forum](https://www.weforum.org/stories/2021/08/5-ways-increase-women-working-ai/)). Within this, women make up about 22%, translating to roughly 66,000 individuals, while men account for 78%, or about 234,000. This distribution, consistent with findings from Deloitte ([Deloitte US](https://www2.deloitte.com/us/en/pages/consulting/articles/state-of-women-in-ai-today.html)) and Forbes ([Forbes](https://www.forbes.com/sites/falonfatemi/2020/02/17/bridging-the-gender-gap-in-ai/)), highlights a significant underrepresentation of women, with regional variations noted—e.g., Eastern Europe (like Latvia) shows nearly 50% female representation, an unexpected detail compared to global averages.

The evidence leans toward this gap being driven by factors such as fewer women pursuing STEM education (only 1.7% of women vs. 8.2% of men graduate with ICT degrees, per UNESCO reports ([UNESCO](https://www.unesco.org/en/articles/does-artificial-intelligence-advance-gender-equality))), cultural stereotypes, and higher attrition rates due to workplace challenges. This imbalance is particularly stark at senior levels, where women hold less than 14% of executive roles, per global tech company data ([MIT Sloan Management Review](https://sloanreview.mit.edu/article/diversity-in-ai-the-invisible-men-and-women/)).

AI Academia: Faculty Representation

In academia, the number of AI faculty positions globally is estimated at around 10,000, based on analyses like the Stanford AI Index Report ([Stanford AI Index Report 2021](https://aiindex.stanford.edu/ai-index-report-2021/)) and surveys from the Computing Research Association ([Computing Research Association](https://cra.org/resources/cra-taulbee-survey/)). It seems likely that women hold about 16% of these positions, or approximately 1,600, with men occupying 84%, or about 8,400. This figure aligns with data showing women making up 18% of AI PhD recipients in North America and 16% of tenure-track faculty in AI-focused roles, per the Stanford report.

The academic gender gap is influenced by similar factors as the workforce, including lower representation in PhD programs (18% women, per CRA surveys) and challenges in retention and promotion. An unexpected detail is the variation in conference authorship, where women constitute only 13.83% of AI paper authors and 18% of presenters at leading AI conferences, per the World Economic Forum ([World Economic Forum](https://www.weforum.org/stories/2022/08/why-we-must-act-now-to-close-the-gender-gap-in-ai/)), reflecting their underrepresentation in high-visibility academic roles.

The Gender Gap: Analysis and Implications

The evidence leans toward a clear and significant gender gap in both sectors, with men outnumbering women by a factor of 3–4 in most contexts. In the workforce, the ratio is approximately 1:3.5 (women to men), and in academia, it's around 1:5.25, based on the numbers above. This gap, while not new, is controversial due to its implications for AI outputs, such as biased generative AI (GenAI) systems that may reflect male-dominated perspectives, potentially reinforcing stereotypes and underrepresenting women's needs.

The controversy lies in balancing diversity goals with legal and ethical considerations, especially given the risks of biased outputs, as noted in reports like UNESCO's analysis on AI and gender equality ([UNESCO](https://www.unesco.org/en/articles/does-artificial-intelligence-advance-gender-equality)). For instance, GenAI tools might prioritize male-centric applications, missing opportunities in areas like women's health, and could erode trust among female users, per Deloitte insights ([Deloitte US](https://www2.deloitte.com/us/en/pages/consulting/articles/state-of-women-in-ai-today.html)).

Detailed Analysis and Methodology

To arrive at these estimates, we reviewed multiple sources, starting with the global AI workforce. Estimates from LinkedIn and IDC suggested around 300,000 AI professionals, with gender distribution data from the World Economic Forum and ArtSmart AI indicating women at 22%, leading to 66,000 women and 234,000 men. For academia, the Stanford AI Index Report 2021 and Deloitte's analysis suggested 10,000 faculty positions, with women at 16%, resulting in 1,600 women and 8,400 men, though discrepancies in percentages (e.g., 22% vs. 16%) required reconciling, ultimately favoring the Stanford report's tenure-track CS faculty data for AI faculty.

Regional variations, such as Eastern Europe's higher female representation, and conference authorship data further highlighted the gap's complexity. The methodology involved cross-referencing reports, acknowledging uncertainties in global estimates, and aligning with the most recent data available as of March 2025.

The gender gap in AI, with women at 66,000 of 300,000 professionals and 1,600 of 10,000 faculty, underscores a critical challenge for legal tech and beyond. At Karta Legal, we advocate for inclusive strategies to ensure AI reflects diverse perspectives, reducing risks like biased outputs and enhancing trust. As AI's influence grows, addressing this gap is not just ethical but essential for equitable technological advancement.

Key Citations

- World Economic Forum on increasing women in AI](https://www.weforum.org/stories/2021/08/5-ways-increase-women-working-ai/)

- Deloitte US on state of women in AI](https://www2.deloitte.com/us/en/pages/consulting/articles/state-of-women-in-ai-today.html)

- Forbes on bridging the gender gap in AI](https://www.forbes.com/sites/falonfatemi/2020/02/17/bridging-the-gender-gap-in-ai/)

- UNESCO on AI and gender equality](https://www.unesco.org/en/articles/does-artificial-intelligence-advance-gender-equality)

- MIT Sloan Management Review on diversity in AI](https://sloanreview.mit.edu/article/diversity-in-ai-the-invisible-men-and-women/)

- World Economic Forum on closing the gender gap in AI](https://www.weforum.org/stories/2022/08/why-we-must-act-now-to-close-the-gender-gap-in-ai/)

- Stanford AI Index Report 2021](https://aiindex.stanford.edu/ai-index-report-2021/)

- Computing Research Association Taulbee Survey](https://cra.org/resources/cra-taulbee-survey/)

- [Girls Who Code website](https://girlswhocode.com/)

- [SHRM on hiring quotas](https://www.shrm.org/topics-tools/tools/hr-answers/can-set-hiring-quotas-to-meet-diversity-goals)

- [NACE on diversity recruiting](https://naceweb.org/public-policy-and-legal/legal-issues/legal-issues-diversity-recruiting/)

- [IBM AI Fairness 360](https://www.ibm.com/cloud/ai-fairness-360)

- [ACLU on inclusion targets](https://www.aclusocal.org/en/inclusion-targets-whats-legal)

- [Salt Lake City Tribune on female-only scholarships](https://www.sltrib.com/religion/2021/08/06/qa-why-theres-debate-over)

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