Key Takeaways
- Women entrepreneurs in the US receive only 2.3% of total VC funding in 2023
- Globally, women receive 0.4% of VC investments per 2022 Crunchbase data
- In Europe, women founders get 1% of VC funding in 2023
- Globally, 70% of women entrepreneurs cite lack of funding as top barrier per GEM 2022
- Women face 2x higher rejection rates for loans than men worldwide
- In US, 42% of women entrepreneurs report gender bias in funding
- Women-led startups in the US grew revenue 2.5x faster than all startups from 2019-2023
- Women-owned businesses in the US employ 13 million people in 2023
- Globally, women entrepreneurs create 150 million jobs annually per ILO 2022
- Women represent 37% of all entrepreneurs in the United States as of 2023
- Globally, 131 million women are business owners according to 2021 estimates
- In the EU, women entrepreneurs make up 34% of all entrepreneurs in 2022
- US governments provide $2B+ in grants for women entrepreneurs annually
- EU WEPs signed by 2,000+ companies supporting women entrepreneurs by 2023
- India’s Stand-Up India scheme funded 1 lakh women since 2016
Despite driving jobs worldwide, women receive less VC and face higher barriers to financing everywhere.
Related reading
Access to Finance
Access to Finance Interpretation
More related reading
Barriers and Challenges
Barriers and Challenges Interpretation
More related reading
Business Performance and Growth
Business Performance and Growth Interpretation
More related reading
Demographics and Prevalence
Demographics and Prevalence Interpretation
More related reading
Support and Policy Impact
Support and Policy Impact 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.
Christopher Morgan. (2026, February 27). Women Entrepreneurs Statistics. Gitnux. https://gitnux.org/women-entrepreneurs-statistics
Christopher Morgan. "Women Entrepreneurs Statistics." Gitnux, 27 Feb 2026, https://gitnux.org/women-entrepreneurs-statistics.
Christopher Morgan. 2026. "Women Entrepreneurs Statistics." Gitnux. https://gitnux.org/women-entrepreneurs-statistics.
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