Hey everyone,

Two things are true about AI and jobs right now, at the same time.

One: workers in the most AI-exposed roles are seeing pay grow 46% since 2021, way ahead of everyone else. Two: US employers have cited AI in over 116,000 announced layoffs this year alone.

Same technology. Same year. Two completely different outcomes depending on where you sit. Let's break down which side of that line you actually want to be on.

Quick programming note before we get into the data: this issue is brought to you by Atlassian, the team behind Jira and Confluence. If you're already using their tools for a class project or a side gig, or curious what real engineering teams run on day to day, worth a look.

AI makes it easier to ship anything, even bad ideas. The hard part is knowing which ideas are worth building.

Jira Product Discovery brings your ideas, customer insights, and priorities into one place, so your team can decide what to ship and move forward with confidence.

Capture ideas, prioritize with evidence, and build living roadmaps your team can rally around—all while staying connected to delivery in Jira, so everyone can see what’s being built and why.

Better product decisions in the AI era.

Try Jira Product Discovery

Indeed's Hiring Lab published new data this week showing advertised pay in the most AI-exposed occupations, think software development, data and analytics, IT, has climbed 46% since 2021. That's well ahead of the 39% average across all job postings and way ahead of the 25% growth in the least AI-exposed roles. Being good with AI is, on paper, paying off.

Here's the catch. When researchers controlled for seniority, most of that premium shrank to 2.4%. Translation: a lot of the "AI pay bump" isn't really about AI skills, it's about senior workers who happen to use AI getting paid senior-worker money. The premium at entry level is described as "much smaller."

Meanwhile, Challenger, Gray & Christmas has tracked more than 116,000 US job cuts this year where employers explicitly cited AI as a reason, about 22% of all announced cuts. Block cut over 4,000 jobs, nearly half its workforce, as part of an AI-driven restructuring. Amazon cut its own AI team in July, months after a 16,000-person layoff in January. Meta tried to shrink teams around AI tooling too, then partially walked it back after it hurt reliability and morale.

What most CS students assume: "learn AI" is a single move that puts you on the winning side of this story.

What the data actually shows: software-development postings are rebounding, but 71% of that growth over the past year came from senior roles. Only 37% of the growth even mentioned AI explicitly in the title. The rebound is real. It's just not mostly happening at your level yet.

Klarna is the cleanest real-world example of the whole issue. Since 2022, the fintech company has cut its workforce by 47%, from 5,527 employees down to 2,907, largely by having AI handle customer service work equivalent to roughly 850 full-time staff. In that same stretch, Klarna raised average employee compensation by 60%, from $126,000 to $203,000, while revenue grew 108% and operating costs stayed flat.

Salesforce is running a milder version of the same play. CEO Marc Benioff has said plainly that AI agents mean the company needs "less heads," and Salesforce cut roughly 5,000 customer service roles across two rounds since September 2025. In that same window, it posted over 1,400 AI-related job openings in a single quarter, a 28% jump year over year, and total headcount is still above 83,000, a company record.

Same companies, same year, both things happening at once: fewer people doing routine, scriptable work, and real money flowing to the people doing the work AI still can't.

Your move: "I know how to use AI tools" is table stakes now, not a differentiator. What actually separates you at the entry level is being able to own a small piece of ambiguous, non-routine work end to end, the exact kind of task that's hardest to automate and hardest to fake on a resume. When you talk about a project, don't just say you used an AI tool. Say what judgment call you made that the tool couldn't make for you.

Not exactly, and the distinction matters. The International Labour Organization's 2026 review found large-scale job displacement is still limited overall, but flagged a real risk: growing inequality and fewer entry-level opportunities as AI changes how work gets organized. The World Economic Forum's broader estimate is that structural shifts, AI included, will create roughly 170 million jobs globally by 2030 while displacing about 92 million, a net gain of close to 78 million. The jobs aren't disappearing. They're shifting toward people who can supervise AI, catch its mistakes, and handle the parts it can't do, and there simply aren't as many of those seats open at the entry level yet as there used to be for junior generalists.

That's the paradox. AI is genuinely raising pay for the people it can't easily replace, and genuinely cutting jobs for the people it can. Which one you are isn't fixed yet. Go check what's open on the job board while you figure it out.

Talk it out with people who get it. Drop your take in r/joblessCSMajors: does this change how you'd describe your own AI use in an interview?