You've probably had the thought: if your company keeps pouring money into AI, your job might be next. A new study of 21,000 companies found the opposite is usually true.

Companies spending the most on AI are growing their teams faster than everyone else, entry-level roles included. Today I'll break down what determines whether AI spending helps or hurts your job security, using the receipts from this study.

Let's get into it.

SK Hynix just pulled off the largest foreign IPO in Nasdaq history. The memory chip maker priced its ADR at $149 a share, raising $26.5 billion and topping Alibaba's 2014 record. The offering was oversubscribed more than seven times, a sign investors are still betting hard on the memory chips that power AI training.

Weekly jobless claims dropped to 215,000, the lowest in six weeks and below the 218,000 economists expected. Claims have stayed in a tight band all year, still no sign of a broad labor market break.

The Fed's June meeting minutes show officials split on which way rates go next. Some members see room to cut, others are bracing for a hike if tariff- and energy-driven inflation sticks around. It was Kevin Warsh's first meeting as chair, and the post-meeting statement was cut to about a third its usual length under his push for less forward guidance.

Kroger agreed to acquire Giant Eagle, consolidating two major grocery chains as the industry keeps bracing for thinner margins and AI-driven supply chain competition from bigger players.

Oracle disclosed in a regulatory filing that AI "resulted, and may continue to result" in workforce cuts. The company shed 21,000 jobs, 13% of its workforce, over the past year, and spent $1.8 billion on restructuring, nearly five times what it spent the year before.

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Ramp and Revelio Labs tracked AI vendor spending against workforce records for 21,559 U.S. companies going back to 2021. They found that firms with the highest AI spending intensity, roughly $30 or more per employee per month within the first three months of adoption, grew headcount by about 10.2% over the following two years.

Light adopters, the companies running a basic chatbot subscription and calling it a strategy, saw no meaningful change in headcount either way. The gap wasn't concentrated at the top either: entry-level hiring at heavy adopters actually grew about 12%, which cuts directly against the fear that AI eats the bottom rung of the career ladder first.

The researchers are careful about what this does and doesn't prove. It doesn't mean AI spending causes hiring. It means companies making real, sustained AI investments right now are growing faster than comparable companies that aren't, and doing it with more people, not fewer.

There's a catch worth sitting with. Almost all of the headcount gains showed up at technology-sector firms specifically, and the study only tracked white-collar roles. The companies pulling this off have capital, technical staff, and management bandwidth that a lot of other employers simply don't have yet, which means the gap between AI winners and AI strugglers is probably going to widen before it narrows.

Why it matters: If your company is spending real money on AI, that's not automatically a threat to your job. It might be the opposite, a sign the company is positioned to grow and needs more people to do it. The distinction that matters is whether your employer is dabbling (a few subscriptions, no real strategy) or genuinely investing (multiple tools, coding agents, a dedicated budget). One of those companies is probably hiring. The other one might be the layoff you read about next month.

More than 110 companies now run paid returnship programs for people re-entering the workforce after a career break, and the list includes some of the biggest names in finance and tech. JPMorgan Chase, Goldman Sachs, Amazon, BlackRock, Dell, Eaton, and Cummins all have active cohorts right now.

These aren't unpaid internships dressed up for adults. Most run 12 to 16 weeks, include structured mentorship and a skills refresh, and lead directly into a full-time offer. Reported conversion rates run above 80%, a far better hit rate than a cold application into a job board.

The programs exist because employers learned something during the last few years of layoffs and hiring freezes. Experienced people who stepped away for a year or two, for a kid, a parent, a burnout reset, still have the judgment and institutional knowledge a fresh grad doesn't, and a structured 12-week runway to prove that is cheaper than a bad hire.

Why it matters: If you've been out of the workforce for a year or more and assumed that gap makes you a hard sell, it doesn't have to. Path Forward's returnship matcher lets you search open cohorts across dozens of partner companies in one place, and a growing number of them are worth applying to even if the starting pay looks conservative going in.

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Before you assume your company's AI spending threatens your job, or before you trust a growth story in an interview, run this prompt in Claude or ChatGPT:

"Search recent earnings calls, press releases, and news coverage for [company name]. Based on what's publicly available, tell me whether they're running a handful of AI subscriptions with no clear strategy, or making sustained, multi-tool AI investments like coding agents, API spend, and a dedicated AI budget line. What's their headcount trend over the last 12 months? Based on that pattern, does this look more like a company growing because of its AI investment, or one using AI as cover for a headcount reduction?"

Run it on your current employer, or on any company before you take a call with them. The gap between "dabbling" and "investing" is exactly what separated the winners from the shrinkers in this week's data.

AI Program Manager: $171,799 average total compensation nationally, per Glassdoor, with a typical range of $143,607 to $209,853 and top earners around $249,857. At AI-native companies the number climbs fast: Technical Program Manager comp at Scale AI runs $190K to $745K with a $234K median, according to Levels.fyi.

It's a clean illustration of this week's Big Story: the companies investing hardest in AI aren't just hiring more, they're paying a real premium for the people running that investment.