Key Takeaways
- In 2022, women represented 26% of all engineering undergraduates enrolled in U.S. colleges and universities, a slight increase from 24% in 2018
- Women earned 25.6% of bachelor's degrees awarded in engineering fields across the United States in the 2021-2022 academic year, totaling approximately 14,200 degrees
- In the UK, female students comprised 21.5% of first-year engineering undergraduates in 2021/22, compared to 19.8% five years prior
- In 2022, the U.S. engineering workforce included 16.1% women, holding about 180,000 of 1.1 million jobs
- Women engineers in the U.S. full-time workforce: 15.8% in 2021, with median age 42 vs. 41 for men
- In the UK, women comprised 12.4% of the engineering workforce in 2022, totaling around 50,000 professionals
- In 2022, women engineering managers U.S.: 12.5% of total, earning median $145,000
- Fortune 500 engineering firms: 8.7% women in C-suite engineering roles in 2023
- In UK, women engineering directors: 9.2% in 2022 FTSE 100 companies
- In 2022, U.S. women engineers retention after 5 years: 45% vs. 65% men
- Early career attrition for women engineers U.S.: 38% leave within 10 years
- UK women engineers leaving profession: 25% within first 7 years 2022
- In 2022, U.S. women engineers earned 92% of men's median salary at $110,000 vs. $119,000
- Early-career women engineers U.S. pay gap: 5% less than men 2022
- UK women engineers median salary: £48,000 vs. £52,000 men 2022, 92% ratio
Globally, women remain underrepresented in engineering, but their ranks are steadily climbing into 2026.
Employment Rates
Employment Rates Interpretation
Enrollment and Degrees
Enrollment and Degrees Interpretation
Leadership and Advancement
Leadership and Advancement Interpretation
Retention and Turnover
Retention and Turnover Interpretation
Salary and Compensation
Salary and Compensation 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.
Stefan Wendt. (2026, February 13). Women In Engineering Statistics. Gitnux. https://gitnux.org/women-in-engineering-statistics
Stefan Wendt. "Women In Engineering Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/women-in-engineering-statistics.
Stefan Wendt. 2026. "Women In Engineering Statistics." Gitnux. https://gitnux.org/women-in-engineering-statistics.
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