AI Jobs Gender Gap: Women Get 26% of Hires

Key takeaways

• Women received 26% of US AI jobs hires in 2025, compared with 50% of hires into non-AI occupations, according to LinkedIn.
• The typical US AI job posting listed about $177,000 in annual compensation, versus $80,000 for a non-AI posting. That $97,000 difference compares job categories; it is not proof of unequal pay for equal work.
• Representation falls again at senior levels: women held 20% of Head of AI roles, 26% of Director of AI roles and 18% of Member of Technical Staff roles.
• For India, where demand for AI engineers is expanding, the practical response is skills-based hiring, paid training and transparent access to career-making projects.

AI jobs are growing quickly, but women are not entering them at the same rate as men. LinkedIn’s latest labour-market analysis found that women accounted for only 26% of US hires into AI occupations in 2025. Women represented 50% of hires into non-AI occupations, making this more than the familiar gender imbalance across technology.

The pay stakes are unusually large. LinkedIn found that the typical US AI job posting listed approximately $177,000 in annual compensation, compared with $80,000 for a non-AI role. The near-$100,000 difference is why the story has become a warning about who benefits from the AI economy. However, it must be read carefully: the figures compare different groups of job postings, not women and men doing identical work.

The central finding: women are underrepresented both where AI jobs begin and where their pay and decision-making power are greatest, so today’s training and hiring choices could shape tomorrow’s income and leadership gaps.

What LinkedIn found about AI jobs

LinkedIn published the research on 18 August 2026 using member employment histories across 24 countries and US job postings from 2023 to 2026. It defined AI talent as people in AI-classified occupations or people demonstrating at least two AI engineering skills. That methodology matters because the study is not counting everyone who occasionally uses a chatbot at work.

The company said US AI job postings had roughly doubled since 2023. AI Engineer had overtaken Machine Learning Engineer as the most common AI occupation on the platform, while postings for Vice President of AI had grown about sixfold. Demand is therefore spreading from model-building roles into implementation, product and leadership work.

For every 100 people newly hired into AI jobs, about 26 were women. The comparison group is striking: women represented half of non-AI hires. LinkedIn also found that women’s share in AI roles was about 10 percentage points below their share in non-AI roles, suggesting that the gap cannot be explained only by women’s overall participation in work.

The research supports a wider trend already visible in India. Lapaas Voice recently reported that AI engineering jobs in India were growing 51% annually, as companies moved from experiments to deployment. A fast-growing market can create mobility, but it can also lock in unequal access if employers repeatedly recruit from the same narrow networks.

AI jobs pay more, but the $100,000 claim needs context

The LinkedIn data shows a large pay premium across job postings. Typical listed compensation was about $177,000 for AI occupations and $80,000 for non-AI occupations, a difference of $97,000 a year. Fortune described this as women potentially leaving roughly $100,000 on the table when they are shut out of the AI job boom.

That framing captures the scale of the opportunity, but it should not be mistaken for a controlled gender pay comparison. AI jobs often require different experience, education and responsibilities from the typical non-AI role. LinkedIn normalized annual compensation and used the midpoint of reported salary ranges, but it did not say that every person who gains an AI skill receives a $97,000 raise.

LinkedIn measure	2025–26 finding	What it means
Women’s share of US AI hires	26%	About one in four new hires
Women’s share of non-AI hires	50%	Gender balance in the comparison group
Typical listed AI compensation	$177,000	Annualized midpoint across AI postings
Typical listed non-AI compensation	$80,000	Annualized midpoint across non-AI postings
Difference between posting groups	$97,000	Opportunity gap, not an equal-work wage gap

The more defensible conclusion is about access. If women are less likely to enter the occupations with the strongest pay, they are less likely to receive the associated promotions, equity and leadership opportunities. An early hiring gap can compound over years even when every company follows equal-pay rules within the same role.

The gap gets wider in AI leadership

Women’s representation drops in several of the most influential AI jobs. LinkedIn reported that women held 20% of Head of AI roles, 26% of Director of AI roles and 18% of Member of Technical Staff positions. Across 27 countries, women held only 13% of C-suite AI leadership roles at AI companies.

This leadership gap affects more than salaries. Senior AI leaders decide which products get built, which risks receive attention and whose experiences are represented in training data and product design. A narrower group of decision-makers can produce blind spots even when the underlying technology is sophisticated.

LinkedIn called the pattern a “triple penalty”: women are less represented in AI occupations, at AI-focused companies and in the leadership of those companies. The penalties overlap. A woman who misses entry-level AI experience is less likely to build the record later used to select directors and executives.

Why women can face both sides of AI disruption

The hiring gap sits beside a second risk. CBS News cited Brookings research showing that women make up 86% of 6.1 million US workers in clerical and administrative occupations that are highly vulnerable to automation and have limited ability to adapt. The International Labour Organization has similarly found that female-dominated occupations are almost twice as exposed to generative AI as male-dominated occupations.

Exposure does not mean every job disappears. In many workplaces, AI will change tasks before it removes entire roles. Yet workers need time, tools and employer-supported learning to move from exposed work into jobs that design, supervise or benefit from automation.

This creates a two-sided policy problem: women could be overrepresented in work transformed by AI while remaining underrepresented in the AI jobs receiving the strongest pay premium. Training only unemployed people after disruption would arrive too late. Employers need to build transitions while workers are still in their current roles.

What employers can change in AI jobs hiring

Skills-based hiring is one practical lever. LinkedIn told CBS News that employers can widen the pipeline by assessing applicable skills rather than filtering mainly by degrees and previous job titles. Someone can demonstrate AI capability through projects, internal work and short courses without having held an “AI” title before.

Companies should also audit who receives paid training, protected learning time and the first chance to work on AI projects. Offering a course to everyone is not enough if only employees with spare time can complete it. Access should be measured by gender, level, department and promotion outcome.

Structured interviews can reduce the influence of confidence and referrals. Every applicant should face the same work sample, scoring guide and job-related questions. Employers can publish the minimum skills actually required instead of copying an inflated wish list that deters capable candidates.

Technical governance matters too. As projects rely more on generated software, companies need people who can review and test it. Lapaas Voice’s reporting on Oracle’s proposed restrictions on AI-generated OpenJDK contributions shows that judgement, testing and accountability remain valuable even when code production becomes easier.

What the AI jobs gap means for India

The LinkedIn pay figures are US figures and should not be converted into an Indian salary promise. India has different wages, industries and education pathways. The relevant lesson is structural: when a fast-growing skill receives a pay premium, unequal access to that skill can widen income differences.

Indian employers have an opportunity to act earlier. Large IT-services firms, banks, retailers and global capability centres already train employees at scale. They can connect AI courses to real assignments, publish selection criteria and make promotion credit explicit. Apprenticeships can also give graduates and career returners verifiable experience.

Workers should focus on proof rather than tool collecting. A useful portfolio might show how a person automated a report, evaluated model errors, protected customer data or reduced processing time. Familiarity with one chatbot is less durable than the ability to define a problem, verify an answer and explain a business outcome.

The market is still small relative to total employment, as Axios noted, but it is influential. The rules developed for AI jobs now may spread into finance, healthcare, manufacturing and media as AI becomes part of ordinary work.

What to watch next

The next test is whether hiring shares improve as training expands. Useful measures include women’s share of applicants, interviews, hires, AI project assignments and promotions. Leadership numbers should be tracked separately because a balanced entry pipeline does not automatically produce balanced decision-making.

Pay data also needs careful monitoring. Companies should distinguish the premium attached to a job category from unequal pay within the same role. Transparent salary bands can make both problems easier to see.

LinkedIn’s 26% figure is therefore a warning, not a verdict. AI jobs are still being defined, and employers can redesign entry routes before exclusion becomes entrenched. The organisations that train existing workers and recruit by demonstrated skill will gain a broader talent pool while reducing a long-term economic risk.

FAQs

What percentage of AI jobs hires were women?

Women accounted for 26% of US hires into AI occupations in 2025, according to LinkedIn. They accounted for 50% of hires into non-AI occupations.

Do AI jobs really pay $100,000 more?

LinkedIn found typical listed compensation of about $177,000 for AI job postings and $80,000 for non-AI postings, a $97,000 difference. It compares different job groups and does not prove that every AI skill produces a $97,000 raise or that women receive less pay for identical work.

Why are women underrepresented in AI leadership?

The gap develops across several stages, including access to technical roles, AI-focused companies, high-visibility projects and promotion pipelines. LinkedIn found women held only 13% of C-suite AI leadership roles at AI companies across 27 countries.

How can employers close the AI jobs gender gap?

Employers can use skills-based assessments, paid training, transparent project allocation, structured interviews and published salary bands. They should measure hiring and promotion outcomes rather than only counting course enrolments.