Thought 005 · Read · 3 min · July 22, 2026

AI became a verb.

AI stopped being something companies have. In their own letters, it became something they do — and something that does.

Prompted by Netflix’s Q2 2026 shareholder letter and a broader census of S&P 500 shareholder letters.

Netflix says it is “leveraging technology to improve every aspect of our service and our business.”

I wanted to know what that actually meant — so I read the letter. Three AI use cases: natural-language search, so members can find things in plain words; GenAI across roughly 300 titles, mostly in post-production; and AI running through its ad business. Find it, make it, sell it.

That got me curious. What is everyone else saying they do with it?

So I pointed a multi-agent workflow at the S&P 500 and had it read every qualifying shareholder letter since Q3 2025. The interesting part wasn’t how often AI showed up. It was what they said it was doing.

Writing code. Settling claims. Finding fraud. Documenting patient visits. Taking restaurant orders. Designing proteins. Planning inventory.

A four-stage timeline showing AI moving from a capability companies had, to copilots people used, to systems that act, and toward people building the actors. BNY reports nearly half its employees are building agents; Repsol is scaling toward 90 agents across more than 3,000 people. A data rail shows 194 cases that inform, 138 that assist, and 66 that act.
The dominant story moved from capability to copilot to autonomous action. The pioneers suggest the next shift is people building the actors.

The letters trace an arc. First companies had AI — an investment, a capability, a line on a slide. Then people used it. Microsoft points to Mercy, where its tools saved caregivers more than 100,000 hours documenting physician visits. The AI takes the notes; the caregiver stays with the patient.

Now AI acts. The line that matters isn’t what the system knows anymore — it’s what it’s trusted to change. And then a few go further: the people closest to the work start to build the actors themselves.

Signals from the edge

The frontier is delegated authority.

The frontier begins when an AI system is trusted to change something that matters. These are the clearest signals in the letters of AI crossing from advice into action, authority, and the physical world.

  1. 01
    Changes the reservation

    Airbnb

    Its assistant lets guests cancel or change reservation dates in chat. The latest letter says more than 40% of support issues are resolved without a human.

  2. 02
    Changes production code

    Block

    Builderbot runs more than 200,000 operations a day and makes 15% of production code changes nearly fully autonomously. A person still makes the final push decision.

  3. 03
    Spends under delegated intent

    Visa + Mastercard

    Visa gives agents payment credentials. Mastercard makes an agent’s purchase traceable to the human instruction behind it.

  4. 04
    Moves through the physical world

    Tesla

    Tesla reports unsupervised Robotaxi rides in Dallas and Houston, while paid Robotaxi miles nearly doubled sequentially in Q1.

  5. 05
    Builds an agent workforce

    BNY + Repsol

    Nearly 50% of BNY employees are building agents; 134 digital employees already operate alongside colleagues. Repsol is scaling from 22 custom agents toward 90 across more than 3,000 employees.

An editorial selection from the 398 cases, not a ranking. What connects them is not the model. It is the authority each system has been given.

The job is shifting from do the work.It’s becoming build the thing that does the work.

That’s the shift I’d watch. Not how much AI a company can list — anyone can list. Whether it can name the work precisely enough to pick the right tool, and set the boundaries around what that tool is trusted to do.

The evidence beneath the thought

The reading rests on a census of 398 specific AI use cases named by 109 companies in shareholder and CEO letters reporting on Q3 2025 or later. Every case, with its source, is browsable by theme, sector, and language in the standalone evidence explorer. It is a census of what companies describe — not a complete measure of AI adoption; the ten-theme grouping is an analytical overlay.

Source behind the reading

The opening examples come from Netflix’s Q2 2026 shareholder letter. The wider research set covers shareholder and CEO letters reporting on Q3 2025 or later. Not every S&P 500 company publishes a qualifying letter. The evolution framing, pioneer selection, and explorer themes are analytical overlays, not categories used by the companies themselves.

How this was made

The research set was assembled through a multi-agent workflow in Claude — one agent per company, sweeping qualifying letters. The piece was first drafted and built with OpenAI Codex (GPT-5), then revised and edited with Claude Code (Claude Opus 4.8), July 2026. AI did the searching, comparison, and construction; the reading, the selection of pioneers, the framing, and the final judgment are mine.

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