Women Made Up 26% of New U.S. AI Hires

Women accounted for 26% of new U.S. AI hires in 2025, compared with 50% of hires in non-AI occupations, according to LinkedIn data released August 18. The findings show an even wider gender gap in some technical and higher-paying roles, offering a closer look at where women in AI jobs remain underrepresented.

Key Takeaways

• Women represented 26% of new U.S. AI hires in 2025, while men accounted for 74%.
• Women made up 50% of new hires in non-AI occupations during the same period.
• Men accounted for 82% of new hires for member of technical staff roles.
• Median listed pay for member of technical staff positions reached $223,000 in 2026.
• Data annotator hiring was roughly evenly divided between men and women, with median listed pay of $51,000.

LinkedIn’s latest hiring data shows a sharp difference between women’s representation in artificial intelligence roles and their share of hiring elsewhere in the U.S. labor market.

Women accounted for 26% of new AI hires in 2025. Men accounted for the remaining 74%. By comparison, women represented 50% of new hires across non-AI occupations.

That 24-percentage-point difference places the gender gap in AI hiring at the center of LinkedIn’s findings.

The figures refer to people entering AI roles during 2025 rather than the overall composition of the existing AI workforce. LinkedIn based its hiring analysis on member employment profiles, while compensation figures were drawn from U.S. job listings.

The findings arrive as AI-related employment expands across technical, research, engineering and data-focused positions. LinkedIn describes many of those jobs as among the faster-growing and higher-paying opportunities in the labor market.

The hiring disparity also adds another dimension to the broader gender pay gap in tech, particularly as some specialized AI roles command significantly higher listed compensation.

Technical AI Roles Show an Even Wider Gender Gap

The disparity becomes more pronounced in some specialized technical positions.

Member of technical staff roles provided one of the clearest examples in LinkedIn’s data. Men accounted for 82% of new hires into those positions in 2025, leaving women with an 18% share.

The role is common in AI laboratories and often combines elements of advanced research and full-stack engineering. That places it within the more technically specialized side of artificial intelligence development.

The 18% female share is below women’s 26% representation across new AI hires overall, showing that the gender distribution varies considerably by occupation.

Compensation also makes the difference notable. Median listed pay for member of technical staff positions reached $223,000 in 2026.

LinkedIn’s compensation figures are based on job postings, not salaries reported by individual workers. The $223,000 figure therefore represents median listed compensation rather than the earnings of every person working in the role.

Higher-Paying Roles Tend to Have More Male Hires

LinkedIn’s data points to a relationship between compensation and gender representation across the AI roles included in its analysis.

Member of technical staff positions illustrate that pattern. Men received 82% of new hires in 2025, while median listed compensation for the role reached $223,000 in 2026.

The findings do not establish that every higher-paying AI occupation has the same gender distribution. They do show that several prominent technical roles with higher listed compensation have comparatively low female representation.

That distinction matters because the hiring gap is not simply about the number of people working in artificial intelligence. It also concerns which workers are entering positions associated with higher compensation, technical responsibility and potential career advancement.

LinkedIn has separately reported that women remain underrepresented in technical and leadership positions across the technology industry.

Sarah Steinberg, LinkedIn’s head of global public policy partnerships, highlighted the potential consequences in a statement to Axios.

“Women may be included in the AI economy, but not in the roles most likely to drive long-term economic mobility, leadership, and decision-making power.”

Her comments place the hiring figures within a broader discussion about access to higher-paying technical and decision-making positions.

That issue also intersects with the wider conversation around women in tech leadership, where representation often narrows as roles become more senior or specialized.

Data Annotation Shows a Different Hiring Pattern

Not every AI-related occupation shows the same gender split.

Data annotator positions were approximately evenly divided between men and women, according to the LinkedIn data. Median listed compensation for those roles was $51,000.

That creates a marked contrast with member of technical staff positions, where 82% of new hires were men and median listed pay reached $223,000.

The comparison illustrates how broadly the term “AI job” can apply. Artificial intelligence employment includes positions ranging from data preparation and annotation to advanced engineering, research and leadership.

As a result, women’s 26% share of overall AI hiring does not describe every occupation equally.

The data instead suggests that representation differs according to the type of work, with women approaching parity in some roles while remaining substantially underrepresented in others.

The Hiring Gap Extends Beyond a Single Occupation

LinkedIn’s findings show that the gender gap in artificial intelligence cannot be explained by one job category alone.

Across all new U.S. AI hires in 2025, women held a 26% share. That compares with their 50% share of new hiring across non-AI occupations.

Within individual AI roles, however, the numbers can look substantially different.

Data annotation was close to an even gender split. Member of technical staff hiring was heavily male. LinkedIn’s broader research also points to continuing underrepresentation of women in technical and leadership positions.

The data therefore presents two related issues. Women are entering AI roles at a lower rate than non-AI occupations overall, and their representation can fall further within some highly technical positions.

AI employment also remains only one part of the broader U.S. labor market. The figures should therefore be read as measures of hiring within AI occupations rather than women’s representation across all American jobs.

LinkedIn’s Data Highlights Where the Divide Is Widest

The findings provide a more detailed picture of the gender gap in AI hiring by separating overall hiring from individual occupations and compensation levels.

Women represented 26% of new U.S. AI hires in 2025, but the distribution ranged from roughly half of data annotator hires to 18% of member of technical staff hires.

The compensation difference between those roles was also substantial, with median listed pay of $51,000 for data annotators and $223,000 for member of technical staff positions.

Those figures do not explain the causes of the hiring gap. They do show where the disparity is most visible and why the composition of individual AI occupations matters when evaluating women’s participation in the sector.

The LinkedIn data suggests that representation cannot be measured by participation alone. The type of role, its technical responsibilities and its compensation provide additional context for understanding who is gaining access to different parts of the AI labor market.

Frequently Asked Questions

What percentage of new U.S. AI hires were women in 2025?

Women accounted for 26% of new U.S. hires for AI roles in 2025, according to LinkedIn data. Men accounted for 74%, while women represented 50% of new hires in non-AI occupations.

What does the data show about women in AI jobs?

The data shows that women in AI jobs remain underrepresented in new U.S. hiring compared with non-AI occupations. Representation also varies by occupation, with a substantially smaller female share in some specialized technical roles.

What percentage of member of technical staff hires were women?

Women represented 18% of new hires for member of technical staff positions in 2025, while men accounted for 82%. Median listed pay for those positions reached $223,000 in 2026.

How does data annotation compare with technical AI roles?

Data annotator hiring was approximately evenly divided between men and women, with median listed pay of $51,000. That contrasts with member of technical staff positions, where 82% of new hires were men and median listed pay was $223,000.

Does the data show why the gender gap exists?

No. The figures describe hiring patterns, representation and listed compensation rather than establishing the causes of the disparity. They show that women’s representation differs significantly across AI occupations.