Short Your Own Product

How to fix per-seat pricing in the age of AI

In 2024 Salesforce launched its AI agent and priced it at two dollars a conversation. Customers hated it - not the agent, the meter. You couldn’t tell what a month would cost, so you couldn’t sign, and by May 2025 Salesforce had walked the price back to a system of credits. The most-watched AI product of the year had its price tag redesigned twice before anyone trusted it.

That flailing is not a Salesforce problem. It is what happens to everyone who builds an AI product and reaches for the price tag the whole industry already knows how to use - per seat, per user, per month - which quietly stops working the moment the product is good. An AI tool that does the work of three people invites the customer to buy fewer seats, not more. The better it performs, the less per-seat pricing collects. You end up short your own product.

Per-seat was always a proxy

For twenty years that was a safe bet, because a seat was a fair stand-in for value. Software was a thing a person operated, so one human meant one licence meant one slice of work, and a company that grew bought more seats. Salesforce, Slack, Zoom - everyone priced by the headcount logged in, and it held because headcount and value rose together.

The model never actually measured the value. It measured the people standing next to the value, and trusted the two to stay in step.

AI is the thing that pulls them apart. When the work stops needing the worker, the seat stops tracking anything. The value keeps arriving; the head it was billed to does NOT - and a price tied to heads starts shrinking at the exact moment the product gets good.

Seat, usage, outcome, and where each one snaps

So the price goes looking for something else, and there are only three places to grab. Charge by the seat and you bill for a login. Charge by usage - tokens, calls, conversations - and you bill for the work the tool does. Charge by outcome - a resolved ticket, a booked meeting - and you bill for the result itself. Each one fixes the seat problem and breaks something new.

Which one fits turns on a single fact about your product: does it help a person, or replace one? A copilot that makes a salesperson faster still has a person in the seat, so per seat holds. An agent that closes the ticket with nobody watching has cut the person out, and the seat with them. Augmentation keeps the seat. Automation kills it. Most arguments about AI pricing are really about which of those you built.

Find the unit that moves with the value

Underneath it all sits one question, worth asking before you price anything: what is the unit that moves when your customer gets value? Find that, and you have what to charge for. Three checks get you there.

The first is the decoupling. Does your value still track headcount? If the pitch is “do the same work with fewer people,” it doesn’t, and per seat is already a slow leak.

The second is the meter. Can you count the unit cheaply, and in a way that survives a renewal meeting? Tokens are easy to count and mean nothing to a buyer; a resolved ticket means everything, and you will argue over what counts as resolved.

The third is the budget. Can the customer predict the bill before they sign? This is the check Salesforce flunked. A meter nobody can forecast is a meter nobody buys.

Run a product through the three checks and you get its price. Microsoft’s copilot still moves with the user, so it stays a seat at thirty dollars a head. Zendesk and Intercom failed the seat check and found their unit in the resolved ticket, the one thing a buyer can both see and forecast: Zendesk bills around a dollar-fifty for it, Intercom ninety-nine cents, and only when the thing actually works.

Outcome pricing is underwriting in a hoodie

Which makes outcome pricing sound like the answer, and it is the most seductive of the three. Charge only when you deliver, and the customer can hardly argue. But there is a catch the decks skip. The moment you price on the result, you have stopped selling software and started selling a guarantee. If the model has a bad month, you eat it. If the customer’s own process made the bot fail, you argue about whose fault that was. You have walked into the insurance business: pricing risk, holding it, paying out when the result misses. And most software companies have no idea how to run an insurer.

So the market is not settling on pure outcomes. In the year to 2025 the share of software priced purely by the seat fell from twenty-one per cent to fifteen, the pricing analyst Kyle Poyar found, while hybrid - a base you can forecast with usage or outcomes stacked on top - climbed from twenty-seven to forty-one.

So the move, if your name is on the price, is dull, and it pays to make it early. Take the unit your product bills by today, and the unit that actually moves when the customer wins, and hold them up against each other. If they are the same, per seat is fine, and you can ignore everyone telling you it’s dead. If they have drifted apart, you are charging for heads while the value walks out on its own two feet - and a price that shrinks as the product improves won’t wait for the next planning cycle. It quietly bills you for the upside of your own best work, one renewal at a time.