Excluded, S&P Says** Manufacturers have reduced their headcount in three of the past four months.
Concretely, S&P noted that even though the manufacturing index showed better-than-expected results in June, it was largely a result of inventory build.
Chris Williamson, chief business economist at S&P Global Market Intelligence noted that the survey “signals that current output levels are consistent with the economy struggling to grow much faster than a 1% annualized rate in the second quarter.” The outlet recalled that the U.S. economy grew at a 1.6% annualized pace in the first quarter of the year and at 0.5% rate in the second quarter.
GM laid off 1,000 Factory Zero workers. Robots took their jobs.**
Factory Zero was supposed to be the future. GM’s flagship all-electric truck plant in Detroit, capable of producing a Silverado EV roughly every eight minutes, staffed by 4,000 workers at full capacity. That was the pitch. The reality: a single shift, more than 1,000 workers on indefinite layoff, and about 50 brand-new Fanuc cobots rolling onto the assembly line. Unlike traditional industrial robots locked behind safety cages, these machines stand right next to humans, attaching body panels as vehicles move down the track. GM calls it progress. UAW Local 22 calls it a gut punch.
Nonfactory workers are getting the ax too.
The company acknowledged in regulatory filings that the deployment of AI has already contributed to workforce reductions and could continue to do so in the future.
Oracle is aggressively expanding its position in the booming artificial intelligence and cloud infrastructure markets. The company has secured major AI-related contracts and partnerships, including projects involving OpenAI and other large technology customers, while dramatically increasing spending on data centers and computing capacity needed to support generative AI workloads.
I imagine Larry Ellison will get a stock option boost from the savings.
The pattern is consistent: cut costs in traditional operations to fund the massive capital expenditures required for AI competitiveness.
Why Other Companies Doing the Same
Massive AI CapEx Needs: Hyperscalers (Meta, Microsoft, Google/Alphabet, and Amazon) are projecting combined AI-related capital spending of $650–700+ billion in 2026. This funds enormous data center builds, GPU clusters, custom silicon, and power infrastructure. To protect margins and satisfy investors, companies are offsetting these huge investments with workforce reductions and efficiency gains.
Recent Examples Across Big Tech:
Meta: Announced ~8,000–10,000 job cuts (about 10% of workforce) explicitly to free up resources for AI spending (including $115–135 billion in projected 2026 capex).
Amazon: Cut ~16,000 corporate roles in early 2026 (on top of prior reductions), citing streamlining and AI-driven efficiency.
Microsoft: Offered voluntary buyouts to thousands of employees while ramping up heavy AI investments.
Others: Atlassian, Salesforce, Snap, Cloudflare, GitLab, and Coinbase have also announced significant percentage-based cuts tied to AI restructuring.
Investor Pressure + Competitive Race: Wall Street rewards companies that show discipline in non-AI spending while demonstrating aggressive AI bets. Those that fall behind on AI infrastructure risk losing market position in cloud, search, advertising, enterprise software, and more.
I think the auto industry is a bad model for manufacturing reform. Median new car price is $50K. Many traditional customers can no longer afford new. They are keeping cars longer and more likely to buy used.
Meanwhile China is offering new cars for $15K or so. Tariffs will try to keep them out of the US but they will be in Mexico and Canada. Can you keep folks from driving one across the border.
And the promise of EVs seems to have faded. Maybe a shadow of its former self. Companies over invested in anticipation. And now must trim (or sell batteries to use capacity).
Then comes the affect of AI. Not so lilely to affect assembly line workers. (They already have robots in place where they can use them.) The cuts are most likely in the white collar positions where AI means fewer people needed.
Lots of manufacturing is doing some trimming but the auto industry especially has a struggle ahead. It probably won’t survive in present form. Big changes are needed. Its another paradyme shift. (Do you think Boeing will be trimming? With their order backlog, doubtful.)
Different sectors are showing different responses.
AI-related job loss fears grow each time another company announces a round of layoffs. Through May of 2026, companies announced that close to 90,000 job cuts were tied to AI, and, by some accounts, up to 15% of U.S. jobs are projected to be eliminated by AI over the next five years. Promises from the tech industry that AI will also create new jobs does little to ease fears, especially for the generation wondering if anyone will be hiring when they graduate.
A recent report from Ramp and Revelio Labs, which track enterprise AI spend and workforce records from nearly 22,000 companies, respectively, complicates that gloomy narrative.
The report found that companies spending heavily on AI are growing headcount faster, even in the entry-level roles that many fear are doomed. According to the report, “high-intensity adopters” — firms that spend on average $30 per employee per month on AI in the first three months — saw headcount increase 10.2%. Headcount also rose across functions, including engineering, sales, administration, customer service, finance, marketing, and scientist roles.
