Quick Take
- Pega will charge enterprise clients for business outcomes, not for how many AI tokens they burn.
- The global CTO says buyers now ask what value AI returns, not how much AI they deploy.
- India is central: Pega employs about 1,900 people here, its largest single-country workforce base.
In This Article
US enterprise software firm Pegasystems is moving to outcome-based pricing, charging customers for completed business results instead of the volume of AI tokens they consume, the company confirmed in June 2026. Don Schuerman, global chief technology officer (CTO) at Pega, framed the change as a response to buyer frustration with unpredictable AI bills.
The pitch lands as enterprises reckon with what Pega calls the “token tax,” the rising cost of AI agents that reason from scratch on every query. Speaking to The Economic Times from Hyderabad, Schuerman said the buyer conversation has changed. Companies now ask what value they get from AI, not how much AI they can push into every workflow.
StartupFeed Insight
The real signal here is not the price tag, it is where Pega puts the expensive AI. By confining heavy reasoning to the design phase and running cheap, narrow calls in production, Pega decouples its revenue from token inflation. That is a hedge against its own suppliers. Indian GCC leaders and SaaS founders billing global clients should watch closely, because outcome-based pricing only works if you can guarantee a repeatable process. Expect at least two more enterprise vendors to copy this flat-rate, per-case model before PegaWorld 2027, as token costs keep climbing and CFOs demand cost certainty. By Avinash.
What is Pega’s outcome-based pricing shift?
Outcome-based pricing means a customer pays a flat rate for a completed unit of work, such as a processed loan or a resolved case, no matter how much AI runs behind it. Pega calls this billable unit a “case.” Pega’s platform has long metered work this way, which makes the shift a natural fit rather than a rebuild.
Schuerman argues the old meter model punished buyers. The same prompt could cost pennies one day and burn a large share of a monthly budget the next. That unpredictability, he says, pushed clients to demand pricing tied to results they can measure.
About Pegasystems
Pegasystems builds low-code software that helps large enterprises automate business processes and manage customer relationships. Founded in 1983 and headquartered in Waltham, Massachusetts, the firm serves Fortune 500 clients and trades on the NASDAQ. It employs roughly 4,900 people globally, with India making up its single largest share of staff at about 41%, according to Revelio Labs workforce data.
How does outcome-based pricing control AI costs?
Outcome-based pricing controls AI costs by changing where the expensive reasoning happens, not by cutting AI use. Pega pushes exploratory, token-heavy AI into the design and build stage inside its Blueprint tool, where long reasoning is acceptable. At runtime, it uses narrow, governed AI calls that keep consumption predictable.
“There is less chance of the agent spinning off and doing a bunch of stuff I don’t want it to do, less chance of it leading to an outcome I don’t want and less chance of it leading to a cost I don’t want,” Don Schuerman, CTO, Pegasystems.
This design-first discipline is what lets Pega promise a fixed price per case. Because a repeatable process needs little AI to run once it is defined, the company bets its per-case cost stays low even when clients scale up.
Why does the India base matter here?
India sits at the centre of Pega’s build capacity, which makes the outcome-based pricing bet partly an India story. The company employs about 1,900 people in the country, according to The Economic Times, with a large engineering presence in Hyderabad. India also accounts for the biggest slice of Pega’s global workforce.
“We’ve shifted from asking, how much AI can we use and how many agents can we deploy, to asking, what’s the real value we’re getting out of this,” Don Schuerman, VP marketing and technology strategy, Pegasystems.
For India’s engineers, the shift rewards process design skill over raw model tuning. The teams that define clean, repeatable workflows become the ones who protect Pega’s margins under a flat-rate model.
How do rivals price enterprise AI?
Rivals are testing their own answers to the token cost problem, and no single model has won yet. ServiceNow uses a hybrid mix of consumption and outcome tiers, while other contact-centre vendors meter usage in different ways. Pega’s edge is that its per-case billing predates the AI boom.
| Vendor | Pricing Approach | Cost Signal |
|---|---|---|
| Pega | Flat rate per completed case | Predictable, tied to outcome |
| ServiceNow | Hybrid consumption plus outcome tiers | Mixed, tier-dependent |
| Typical AI vendors | Per-token consumption | Unpredictable, meter runs |
What sets Pega apart is architecture, not just the price sheet. Its deterministic runtime lets it absorb the risk of a flat rate that pure token-billing rivals cannot easily match.
What’s Next
Watch Pega’s next quarterly results for early signs of how outcome-based pricing affects annual contract value, which management wants to grow 15% with most revenue from Pega Cloud. If flat-rate deals close faster, expect rivals to follow within a year. Will CFOs trust a per-case price enough to abandon the token meter for good?
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