Key Takeaways
- In 2023, women occupied 10.4% of CEO positions at S&P 500 companies, up from 8.8% in 2022.
- Globally, women hold 27% of board seats in large listed companies as of 2023, with significant variation by region.
- In the US tech sector, women comprise 26% of executive positions in 2023.
- Global tertiary enrollment for women is 55% in 2023.
- In the US, 59% of college students are women in 2023.
- EU higher education: women 54.6% of graduates 2023.
- In the US, women earn 57 cents for every dollar men earn in 2023.
- EU gender pay gap averages 12.7% in 2023.
- Globally, women earn 77% of men's wages for similar work 2023.
- In politics, women hold 26.5% of parliamentary seats globally 2023.
- US Congress: 27.2% women in 2023.
- EU Parliament women: 32.7% 2023.
- US female labor force participation rate was 57.4% in 2023, compared to 69.5% for men.
- Globally, women's labor force participation stands at 49.6% versus 74.5% for men in 2023.
- In the EU, 69.1% of women aged 20-64 were employed in 2023.
Women’s leadership and workforce gains are real, but pay gaps and underrepresentation persist across sectors.
Corporate Leadership
Corporate Leadership Interpretation
Education Attainment
Education Attainment Interpretation
Gender Pay Gap
Gender Pay Gap Interpretation
Political and Public Representation
Political and Public Representation Interpretation
Workforce Participation
Workforce Participation Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Aisha Okonkwo. (2026, February 13). Gender Diversity Statistics. Gitnux. https://gitnux.org/gender-diversity-statistics
Aisha Okonkwo. "Gender Diversity Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/gender-diversity-statistics.
Aisha Okonkwo. 2026. "Gender Diversity Statistics." Gitnux. https://gitnux.org/gender-diversity-statistics.
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