If you graduated in the last few years and you keep hearing that the job market is brutal, here is the twist: it depends entirely on which door you are knocking on. According to a LinkedIn study released this week, the median salary for a typical AI role in the US sits at $177,000, while the median for non-AI roles is $80,000. Same generation, same country, sometimes the same university, more than double the pay.

And this is happening while youth unemployment climbs. In June, the unemployment rate was 7.2% for workers aged 22 to 27 and 5.7% for recent university graduates, compared with 4.1% overall. So the headline is not just “AI pays well”. The headline is that a two-tier market is forming inside your own generation, and the sorting is happening now.

What the LinkedIn study actually found

LinkedIn published on Tuesday a study identifying the 12 fastest-growing AI jobs. The numbers behind it are worth reading slowly, because they explain who is getting hired and who is being left out.

• Gen Z workers make up more than two-thirds of new hires for forward deployed engineer and AI engineer roles, with average annual pay of $199,000 and $166,000 respectively.
• Millennials make up 60% of new hires for head-of-AI positions, with an average salary of $236,000.
• AI job postings on LinkedIn grew 14% between 2023 and 2024, then jumped 156% between 2024 and 2025.
• 91% of workers in AI-related roles hold a bachelor's degree or higher. Nearly half of head-of-AI hires have a master's; 20% have a PhD.

Kory Kantenga, who leads Economics for the Americas at LinkedIn, told CNBC that there is a widespread view in the labour market right now that it is very hard to find a job if you belong to Gen Z. His own data pushes back on the simple version of that story. “It was striking to see them tap into the AI labour market so dynamically,” he said.

The pay gap between AI and everything else

To feel the scale of the gap, compare the AI numbers with what most people your age actually earn. Per Federal Reserve Bank of St. Louis data, the median annual wage for workers aged 25 to 34 was $60,320 in Q2 2026, and $74,672 for those aged 35 to 44.

Put next to a $177,000 median for AI roles, that is roughly triple the pay of a same-age peer in a non-AI job. Kantenga explains the mechanism plainly: a lot of money is being invested in AI right now, and to attract talent, companies have been forced to raise pay significantly.

The other side of the coin is less glamorous. The unemployment rate for recent computer science graduates rose to 7% in 2024, according to the New York Fed. Meanwhile, the class of 2026 in computer science is projected to have the highest starting salary of any major, at $81,535, per the National Association of Colleges and Employers. Translation: a technical degree still opens doors, but the door that leads to the $177,000 bracket is much narrower than the door labelled “tech”.

The gender split, and why it matters if you are a woman entering the field

Only 26% of new AI hires in 2025 were women, compared with 50% in non-AI professions. The imbalance runs the full length of the ladder.

• 20% of head-of-AI hires are women.
• 26% of AI director hires are women.
• 18% of technical staff hires (MOTS) are women.
• The data curator role, the lowest-paid on the list at an average of $51,000, is the only one where women are hired on par with men.

Kantenga puts it bluntly: “women are under-represented at every rung of the hierarchy.” A February 2025 Russell Reynolds study cited alongside the LinkedIn research found women hold only 10% of CEO and top tech positions in AI organisations. If you are a woman considering an AI-adjacent path, that is not a reason to walk away, but it is a reason to plan carefully: who mentors you, which teams you join, whether the company can name women in senior technical roles when you ask.

What this means for you, in practical terms

You do not need to become an AI engineer overnight. But you should understand where the money is flowing before you accept an offer, ask for a raise, or plan your next course.

1. Check the benchmark before you sign

If you have a technical background and you are looking at an offer that touches AI, machine learning, data infrastructure, or MLOps, do not compare it to “what my friends earn”. Compare it to the market for that specific role. A forward deployed engineer role at $199,000 and a general software role at $95,000 are technically both “engineering jobs”. They are not the same negotiation.

2. If AI is not your path, do not panic, but do adapt

The 156% year-on-year growth in AI job postings does not mean every other career is dying. It means the mix is shifting. If you work in marketing, finance, HR, design, or operations, the useful question is not “should I switch to AI?” but “which AI tools are becoming part of my job description in the next 18 months?” Kantenga notes that some workers he speaks to feel positive and see AI as a real career opportunity, while others worry about being replaced. Both reactions are rational. The people who fare best usually stop treating it as a binary.

3. Credentials still matter more than the discourse suggests

91% of AI hires hold a bachelor's or higher. Nearly half of head-of-AI hires hold a master's. If you are early in your studies and drawn to this space, the postgraduate route is not optional decoration, it is the median profile of the person getting hired. That is worth knowing before you decide whether to keep going.

4. Read the room before you accept

A high AI salary does not automatically mean a good workplace. Ask about team composition, workload during model launches, on-call expectations, and whether the company has retained the technical women it hired last year. Employer reviews from people already inside are one of the fastest ways to find out what the offer letter will not tell you.

The bigger picture

The LinkedIn data describes the US market, but the pattern travels. Wherever AI hiring accelerates, three things tend to follow: a very steep pay premium for a narrow slice of roles, a widening gap between that slice and the rest of the same generation, and a gender composition that hardens fast unless someone actively pushes back on it.

If you are 25 and technical, this is one of the best moments in a decade to negotiate. If you are 25 and non-technical, this is the moment to figure out where AI touches your work and to build one specific skill around it. If you are a woman entering the field, the numbers say the ladder is tilted, and that means the questions you ask before you join a team matter more than usual. None of this is destiny. It is just what the market is telling you right now, in real numbers, if you are willing to listen.