In today's issue:

Hit reply and tell me what you think. I read every one.

The Scoop: An NBER-published survey of nearly 6,000 firms found roughly 90% reported zero measurable AI impact on employment or productivity over three years. Meanwhile $725 billion flows to four AI vendors this year, much of it funded by labor cost cuts.

The official story is everywhere. Companies are getting more efficient with AI, so they need fewer humans. Sounds tidy.

Then the NBER survey landed. Nearly 6,000 executives. Three years of data. Headline finding: about 90% of firms reported no measurable AI impact on productivity or employment. The productivity-driven-layoff story doesn't show up in the actual numbers.

If AI isn't moving the productivity needle for most companies, the layoffs are about something else. Budget reallocation. Roughly $725 billion this year is going to four AI hyperscalers (Microsoft, Google, Amazon, Meta), and a lot of that is being funded by labor cost cuts.

Here's the uncomfortable truth I keep landing on. AI is the cover story. Your job isn't being replaced by a model. It's being replaced by capex. The model just made the press release easier to write.

Everyone says AI is replacing jobs because it's so productive. The data says AI isn't moving productivity yet, and capex is being funded by cuts. Same headline, two completely different stories underneath.

So what for you: If you're inside a company doing AI-cited layoffs, ask one question in your next 1:1. "What measurable productivity gain are we attributing to AI specifically?" If they can't answer with a number, you're inside a budget reallocation, not an AI revolution.

Investors face a dilemma. When the S&P 500 finished its worst quarter since 2022 last month, diversifiers like bonds and bitcoin fell too.

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The Scoop: Meta starts companywide layoffs next Wednesday, May 20, cutting roughly 10% of its 78,865-person workforce. The reason cited: AI efficiency. Meta's actual 2026 commitment to AI infrastructure: $115-135 billion.

Here's the math nobody on TV is showing. Meta is laying off about 8,000 people next Wednesday. Meta is also committing $115-135 billion to AI infrastructure in 2026 alone. Even if every laid-off employee carried a full-loaded comp package well into six figures, the savings would still come out to a small single-digit percentage of the AI budget.

The cuts aren't paying for AI. They're branding for AI.

Once you see that distinction, every "AI efficiency" layoff letter from the next six months reads a little differently.

So what for you: If your company says "AI efficiency" and the layoff size doesn't fund even a fraction of the AI bill, you're seeing optics, not productivity.

The Scoop: Federal Reserve research clocks generative AI's average time savings at 5.4% of work hours, roughly 2.2 hours a week. Stanford tracked 200,000 US households and found ChatGPT users spend most of that saved time on leisure, not on skill-building or extra output.

The productivity story gets messier here. Yes, AI saves time. About 2.2 hours a week for the average user, and 9+ for heavy users. But Stanford's data on 200,000 households shows the saved time mostly goes to leisure (TV and scrolling, mostly). Which is fine for individuals.

It just isn't the "AI is making the workforce dramatically more productive" narrative being used to justify capex and cuts.

So what for you: Time saved by AI isn't a productivity gain unless someone reinvests it. Most people don't. The layoff press releases skip that part.

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Three things worth watching:

→ Meta's May 20 letter. Whether the official communication cites a real productivity metric or just "AI efficiency" is the tell. If it's the second, the layoff narrative cracks publicly.

→ Colorado AI Act SB-189. Passed House 57-6 and Senate 34-1 this week. Effective January 2027. The first US state with mandatory disclosure rules for hiring algorithms.

→ Google's reported "mass exploitation" thwart using AI-assisted hacking tools (OpenClaw). AI-as-attack-surface is the most underreported 2026 story.