AI Jobs Pay Double the Salary of Regular Jobs. Women Got 26% of the Hires.

AI jobs pay a lot more than regular jobs. And most of the people getting hired into them are men.

LinkedIn's research arm published new numbers on August 18, 2026 showing the typical AI job posting in the U.S. advertises about $177,000 in compensation. A typical non-AI posting advertises about $80,000. AI job postings have roughly doubled since 2023.

Women accounted for just 26% of U.S. hires into those AI jobs in 2025, according to LinkedIn. Compare that to 50% of hires into non-AI jobs. Women are landing regular jobs at parity. They are getting shut out of the jobs paying more than double.

Across 27 countries, women hold only 13% of C-suite AI leadership roles at AI companies, LinkedIn found. Head of AI positions are 80% male. Director of AI is 74% male. Member of Technical Staff, a top research title at AI labs, is 82% male.

The one AI job where women hold their own: data annotator. LinkedIn and Forbes both flag that data annotation is the only AI occupation with roughly even gender representation, north of 50% women. It's also the lowest-paid, often gig-based work in the entire field, frequently sourced through freelance marketplaces rather than full-time roles.

LinkedIn calls it a 'triple penalty'

LinkedIn's own report describes three compounding gaps, according to HR Brew: women's share of AI roles runs about 10 percentage points below their share of non-AI roles; women's share of the workforce at AI-focused companies runs about 5 points below comparable non-AI companies; and the C-suite gap is roughly 15 points wider than the gap at lower levels.

Even entry-level hiring shows the gap. HR Brew reported women hold less than 30% of AI roles at AI companies, versus 50% of non-AI roles at non-AI companies. CEOs at AI companies are 13.9% female. CEOs at non-AI companies are 19.1% female.

Catherine Fisher, a career expert and VP at LinkedIn, told HR Brew the stakes go beyond a single hiring cycle. 'The people gaining AI experience today are building the skills, visibility, and credibility that often lead to future leadership opportunities,' Fisher said. 'Employers have a real opportunity to think intentionally about who gets access to that experience.'

Two competing explanations

LinkedIn spokeswoman Sarah Steinberg told CBS News the AI boom is 'compounding barriers that women face' in tech broadly, and pointed to a real downstream risk: women are more likely to hold the customer-service and administrative jobs AI is disrupting. CBS cited a Brookings Institution finding that 86% of the 6.1 million workers in clerical roles most vulnerable to AI automation are women.

Jackie Cook, founder and CEO of Momentum Group, offered Moneywise a different, less structural theory. She argues plenty of women are already doing AI-adjacent work, redesigning workflows, building products, analyzing data, without labeling themselves 'AI experts' or applying for jobs with AI in the title. 'Who decides they're qualified enough to apply can shape the applicant pool before hiring even begins,' Cook said.

If the gap is mostly employers screening women out of interviews they're qualified for, the fix is a hiring-process problem. If the gap is mostly women not applying because they don't see themselves as qualified, the fix is a confidence and self-identification problem. LinkedIn's data can't tell you which explanation dominates, because it measures hiring outcomes, not who applied or why they didn't.

Steinberg's proposed fix, shifting toward skills-based hiring instead of credential-based hiring, cuts against one hard fact in the data itself. LinkedIn found 91% of AI workers hold a bachelor's degree or higher, a figure that climbs above 95% for the highest-paid roles like Head of AI and Director of AI. A field this credentialed isn't an obvious candidate for skills-based disruption, whatever the stated intentions.

There's also a fair question about timing. HR Brew noted that DEI-related STEM funding and programming has been cut back in the past two years, and that shrinking remote-work flexibility has pushed some caregivers, disproportionately women, out of the labor force entirely. Economist Erin Cottle Hunt of Reed College told the Oregon Capital Chronicle that as remote work options shrink, 'the old social norms are falling back out.' That's a labor-market trend running alongside the AI hiring gap, not something LinkedIn's report claims caused it.

None of the sources here identify a specific company or hiring manager discriminating against a specific woman candidate. This is an aggregate hiring-outcome disparity, not a proven case of intentional bias, and LinkedIn's report doesn't claim otherwise.

What happens next is on employers. LinkedIn is pushing companies to adopt skills-based screening for AI roles rather than resume-and-pedigree filtering. Whether that actually moves the 26% number, or whether the credentialing wall LinkedIn's own data describes holds firm, won't be visible until the next hiring cycle's numbers come in.