- AI firms are shifting from per-user fees to charging for work done.
- Software firms selling "units of labor" instead of seats can tap new budgets, Goldman Sachs says.
- It comes as high costs of building and running AI are pushing companies to rethink product pricing.
Software companies are changing how businesses pay for AI tools in a shift that could reshape business spending.
Instead of charging based on how many employees use a tool, some AI companies are beginning to price products based on the work they perform, according to a Goldman Sachs note published Wednesday.
"Companies are increasingly positioning their AI workflows as selling a unit of labor or a unit of productivity, which allows them to tap into larger deal sizes and new budget allowances," wrote Goldman Sachs analysts, after they met with around 40 companies across software and internet sectors recently.
This lets companies charge based on value, separating profits from the cost of running AI and helping maintain strong margins, they added.
The approach is already showing up in how companies package their products. Salesforce has introduced "agentic work units," while Workday sells credits tied to "units of work."
It comes as the high costs of building and running AI are pushing companies to rethink product pricing. That means software spending could become less predictable for the customers using these services.
Last month, OpenAI CEO Sam Altman said that AI could eventually be sold more like a utility.
"Fundamentally, our business — and I think the business of every other model provider — is going to look like selling tokens," he said, referring to the units AI systems use to process and price data.
"We see a future where intelligence is a utility like electricity or water, and people buy it from us on a meter and use it for whatever they want," Altman added.
More broadly, the software industry is moving away from monthly "per seat" licenses toward usage-based, pay-as-you-go pricing, a trend Business Insider's Alistair Barr reported in April last year.
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