AI Jobs for Women: We Got 26% of the Hires. They Pay $97,000 More.

Erica Anderson Rooney is an ex-CPO turned executive coach and AI educator on a mission to get more women into positions of power and keep them there. She is the author of The AI Gap (2026), host of the Glass Ceilings & Sticky Floors and AI Voice or Victim podcasts, and NC Chapter Lead for Women Applying AI. Her SNAP and AI Continuum frameworks are taught to thousands of women through CHIEF, WICT, and Fortune 500 leadership programs. She is the sought-after speaker at the intersection of women, AI, and leadership.

Somewhere in your company this quarter, a job went up with the letters AI in the title and a salary that got the link forwarded around the office.

I want you to ask one question about that job. Who got hired into it?

LinkedIn tracked the data: When it comes to AI jobs for women in the United States, we were 26% of the hires last year. In every other kind of job, women were 50% of the hires. The typical AI posting lists pay of about $177,000. The typical posting for everything else lists about $80,000.

That is a $97,000 difference between the two kinds of jobs, and women got about one in four of the bigger ones.

You Did the AI Work All Year. Then the AI Job Got Posted.

Let me describe a woman I think you know. She might be you… I hope it’s not you… but it might be you.

You run operations, or HR, or customer success, or a finance team. For the last year you have been the person who made AI real on your floor. You sat through the vendor demos. You rewrote the workflow. You answered the questions from legal. You trained forty people who were nervous about it and you did it without making anyone feel small.

Your title did not change. Your job description still reads the way it did in 2021. Your pay moved by the standard merit increase year over year.

Then the company posts a role called something like Director of AI Enablement and you check it out. It asks for an advanced technical degree and prior experience in an AI role. You read the list twice, decide you don’t have all the right qualifications they are asking for, so you close that tab and move on.

And then someone else applies. His name is Bob.  Or John.  Or Joe. He has a side project, a certificate, and a manager who told him to go for it, because “why not?”

You're not crazy. You did the exact work that job describes but the posting was written in a way that could not see you, and you believed the posting over your own past year filled with the experiences and skills you have.

That scene is what the LinkedIn numbers look like.

What LinkedIn Counted in 2026

The report is called The Triple Penalty: Mapping the Gender Gap in the AI Economy. It was published in August 2026 by the LinkedIn Economic Graph Research Institute, and Fortune covered it on August 31, 2026.

First, the basic definitions, because they matter later. LinkedIn counts a person as AI talent when their job is classified as an AI occupation, or when their profile shows at least two AI engineering skills. It counts a company as an AI company when at least 10% of its people on LinkedIn are AI talent. A company does not have to be a famous lab to meet that bar.

AI job postings in the United States have roughly doubled since 2023. The typical AI posting lists a base salary of about $177,000, more than double the roughly $80,000 for other roles. (That pay figure comes from LinkedIn's companion report, The AI Talent Divide, also August 2026.)

Women were 26% of the people hired into AI jobs in the United States in 2025. In jobs outside AI, women were 50% of hires.

At the top of the pay scale it gets thinner. Women were 20% of the people hired as Head of AI, 26% of the people hired as Director of AI, and 18% of the people hired as Member of Technical Staff, a title common for the people who build AI systems.

Across 27 countries, women hold 13% of the C-suite AI roles at AI companies.

And the gap starts on day one. Women hold 29% of the entry level AI roles at AI companies. So the excuse that we only need to wait for the pipeline to fill does not hold up. The pipeline is being filled right now, at 29%.

LinkedIn calls it a triple penalty because three separate gaps stack on top of each other. Women's share drops by about 15 percentage points when the role is in the C-suite, by about 10 more when the role is an AI role, and by about 5 more when the company is an AI company. Together they take women from 45% of the people in non-executive, non-AI roles at other companies down to 13% of the AI executives at AI companies.

Why Are Women Not Getting Hired Into AI Jobs?

LinkedIn is careful here. The report describes the gap and stops short of naming one cause. So I am going to give you what the surrounding research says, and then I am going to give you my read after more than fifteen years in HR, including my time as a Chief People Officer.

The first piece is credentials. LinkedIn found that about 91% of AI roles are held by workers with a bachelor's degree or higher, and in the best paid AI occupations that share is above 95%. If you screen on prior AI titles in a field where women got 26% of the hires, you will keep getting the same result.

The second piece is who gets encouraged. A 2026 Lean In survey of 1,000 U.S. adults, reported by Fortune, found that 33% of men use AI daily compared with 27% of women, and that women are 23% less likely to get support from their manager to use AI. Daily use is how a person builds the examples she later puts on a resume. Manager support is how she gets the time and the cover to do it.

The third piece is how women feel about AI in the first place. Pew Research Center surveyed 5,119 U.S. adults in February 2026 and found that 33% of women expect AI to affect them personally in a negative way over the next 20 years, while 17% expect a positive effect. For men those numbers were 27% and 29%. I think women's caution is earned. But caution reads as hesitation in a talent review, and hesitant people rarely get named to lead the new thing.

Now my read. In my experience, the decision about who gets an AI job is made well before the job is posted. It is made when a leader decides what the role is called. It is made when someone copies the requirements from another company's posting. It is made in the hallway conversation where a manager tells one person, "You should throw your name in for this."

By the time the posting is public, the shortlist often exists in somebody's head.

This exact thing happened to me (in my favor believe it or not!) With a little bit of good timing on my part, I reached out to an HR Director at a company I was eyeing because they had a new HR role posted that looked interesting.  The director took a meeting with me, and after chatting, here is what I know happened behind the scenes.

I wasn’t qualified for the position that was posted, but they had another one in mind that had not yet been created, but they felt I was the right person.  (To be fair - it was the perfect position for me… employee engagement… a role all about high energy and interactions with the employees.  It really was tailor made for me.)  But here is what happened.  They called me and said “We are posting the position for one hour.  Please apply and let us know when you do.”  They posted.  I applied.  They closed the requisition and I got the role.  No one else even had a chance. I learned there that sometimes, you do hire on vibes.  I was the lucky one that was tapped, and it was never truly posted for anyone else.

The Seat I Used to Sit In Is 70% Women. It Is Left Out of the AI Count.

One finding in this report hit close to home.

LinkedIn looked at C-suite seats one at a time. Women hold around 70% of Chief People Officer roles and around 45% of Chief Marketing Officer roles, and those shares barely move at AI companies. Then the report adds a note: these are generally not AI roles.

Compare that with the seats that are counted. Women hold 9.1% of Chief Technology Officer roles at traditional companies and 9.3% at AI companies. Women hold 19.1% of CEO roles at traditional companies and 13.9% at AI companies.

I was a Chief People Officer. So let me tell you what the person in that seat decides in 2026. She decides whether an AI tool screens the resumes. She decides whether AI scores performance reviews, and what happens when it scores them wrong. She decides who gets retrained and who gets a severance letter when a team's work is automated. She writes the policy for what employees may and may not put into a chatbot.

That is AI work. It carries authority over other people's pay and jobs. And in the way the labor market currently labels things, it sits outside the category that pays $177,000.

LinkedIn had to draw a line somewhere, and it drew the line at engineering skills. That is a fair method. Here is what it means for you. If your AI work lives in a job that nobody has labeled as AI, the market cannot find it and your company will not pay for it. The label is where the money is attached.

Which brings me to what you can do about it. Four moves, and you can start all four this month.

AI Jobs for Women Who Do Not Write Code: Get the Words on the Record

Start with your own paper trail. Open your job description, your internal profile and your LinkedIn profile, and look for the letters AI. If they are missing, you have been doing unlisted work.

Write down what you did in plain, specific terms. "Led the rollout of an AI drafting tool to a 60 person claims team." "Chose the vendor and wrote the usage policy." "Built the review step that catches errors before a customer sees them." Use your real numbers and your real team size.

Then ask your manager and HR, in writing, to update your job description to match. This is a small request that changes how you are searched for, leveled and paid. Recruiters and internal talent systems search on skills and titles. They cannot surface what was never typed in.

Sarah Steinberg of LinkedIn told CBS News in August 2026 that "someone can have AI skills without having a related diploma or having held a previous job in AI." I agree with her. You have to make those skills visible in the places where hiring decisions get made.

Ask Who Wrote the Requirements

This one is for every woman who has hiring authority, sits on an interview panel, or approves a requisition.

The next time an AI role crosses your desk, read the requirements line by line and ask where each one came from. Is the advanced degree there because the work needs it, or because the template had it? Does "prior experience in an AI role" describe anyone at all inside your company?

Steinberg told CBS News that moving from hiring on credentials to hiring on skills could bring more women into these jobs. In practice that means swapping a line like "master's degree in computer science required" for "has put an AI tool into daily use on a team and can show the results." The second line describes the job. It also describes a lot more women.

Then ask for the candidate slate before interviews begin. If it is all men, send it back. A search that runs one more week costs far less than an AI leadership team with no women on it.

Put a Woman's Name Forward Before the Job Is Posted

Remember the Lean In finding: women are 23% less likely to get manager support to use AI. You can be the manager who closes that for the women on your team.

This month, name one woman for the AI pilot, the vendor selection committee or the steering group. Say her name in the meeting where the list is made, and follow it with an email so it is on record. Do it for the senior manager who has been quietly excellent, and do it for the analyst in her first job, because the 29% figure tells us the gap opens at entry level.

And do it for yourself. Tell your boss, in a sentence, which AI role you want. "When we create a lead for AI in our function, I want to be considered, and here is what I have already delivered."

If you want to hear why women are still so scarce in tech leadership and what helps, listen to my Glass Ceilings & Sticky Floors conversation with Anna Radulovski, Shattering the Silicon Ceiling. And if the pattern of being passed over while you wait to be noticed sounds familiar, the HER Collective piece on the performance versus potential promotion gap explains why it keeps happening.

Read the Pay Band Before You Take the AI Title

One more finding, and it is a warning. LinkedIn found that the most gender balanced AI occupation is Data Annotator, where women are more than half of the hires. It is also the AI occupation with the lowest pay.

The report also found a pattern across AI occupations: a 10 percentage point increase in the share of men among hires goes along with roughly $45,000 more in median listed pay. LinkedIn is clear that this is a correlation and does not prove cause. Still, I spent more than fifteen years in HR, and I know what it looks like when the work women do gets sorted into the lower band.

So when someone offers you an AI title, read what comes with it. "AI champion" and "AI ambassador" added on top of your current job, with no change in level or pay, is extra work with a nice name. Ask four questions before you say yes. What is the pay band? What level is it? What budget do I control? What decisions are mine to make?

If the answers are none, none, none and none, you have your answer. Negotiate for the version of the role that carries authority and pay, or ask what it would take to get there in six months and get that in writing.

What This Means for Women's Pay Over the Next Ten Years

The Economic Policy Institute reported in March 2026 that women were paid 18.6% less per hour than men in 2025, after controlling for education, age, race and ethnicity, marital status and state. In 2024 that figure was 18.0%, the lowest on record. The gap got wider.

Now add a brand new category of work that pays more than double and is hiring women at 26%. LinkedIn also found that women's share of Member of Technical Staff roles fell from 23% in 2021 to 19% in May 2026. In the best paid part of this field, we are losing ground while the field grows.

AI is a power shift. The people in these jobs decide how AI gets used on everyone else's hiring, reviews and pay. I want women holding that authority, and I want them paid at the $177,000 rate for holding it.

What I Want You to Take From This

Get your AI work named, on the record, and attached to a pay band. An engineering degree is optional for all of it.

Update your job description. Question the requirements on the next AI role you see. Put one woman's name forward this month. Ask the four questions before you accept an AI title.

Every one of those is a decision about pay and authority, and every one is within your reach this quarter.

If you want the full picture of how women get written out of this technology and what we do about it, that is why I wrote The AI Gap. It is my case for why women need a hand in how AI gets built and used at work, and how to start whether or not you have ever written a line of code. Get your copy and bring it to your next leadership meeting.

The future of work will not wait for women to feel ready, and you are more ready than that job posting told you. I am cheering you on.

Erica

Frequently Asked Questions

How many AI jobs go to women?

In the United States in 2025, women were 26% of the people hired into AI jobs, compared with 50% of the people hired into every other kind of job. That comes from LinkedIn's 2026 report, The Triple Penalty. Across 27 countries, women hold 13% of the C-suite AI roles at AI companies.

Why are women not getting hired into AI jobs?

LinkedIn's report measures the gap and does not name one cause. The research around it points to two things: degree and credential requirements written into the postings, and managers who support men's AI use more than women's. My own read, after more than fifteen years in HR, is that new roles get filled by whoever was already tapped for the pilot. This is the AI Gap showing up at the point of hire.

Do I need a technical degree to get an AI job?

Most people in AI roles today have one, and LinkedIn found that about 91% hold a bachelor's degree or higher. LinkedIn's own spokeswoman has said AI skills can be built through courses, training and hands-on use of the tools, and that hiring on skills would bring more women in. If you have run an AI rollout, chosen a vendor or written the rules for how your team uses it, you have AI experience. Get it written into your title, your job description and your profile.