Hybrid pricing has become the most popular model in B2B software, accounting for 37% of companies surveyed, according to Kyle Poyar's Growth Unhinged 2026 survey on B2B monetization published by The VC Corner. The shift away from traditional seat-based pricing accelerates as AI agents automate work with fewer user logins, forcing vendors to charge instead for the work their software performs through usage, resolution, or outcome models. The report examines how the arrival of AI is fundamentally reshaping how B2B companies monetize their products.
Just twelve months ago, only 25% of B2B companies used hybrid pricing, meaning the model gained 12 percentage points in a single year. The survey also found that respondents believe investors prefer hybrid pricing at 35%, compared to just 5% for seat-based models. Meanwhile, companies are feeling budget pressure: Zylo's 2026 SaaS Management Index shows average SaaS spending per organization climbed 8% to $55.7 million, while the number of applications barely budged at 305. A separate Redpoint survey of 141 CIOs found that 45% now fund AI directly from existing software budgets, and 54% are actively consolidating vendors. Among larger companies, 29% of B2B firms above $150 million in annual recurring revenue still depend on seat pricing, but the majority of overall respondents are actively rethinking how they price AI features.
The report identifies three emerging pricing models that charge for work performed rather than logins: usage-based pricing charges customers for what they consume, similar to electricity, and companies like Stripe, Twilio, Snowflake, Databricks, and MongoDB have used this approach for years. Resolution pricing bills per completed job, such as a processed invoice or a support ticket closed by AI, with both vendor and customer seeing the same countable event. Outcome pricing goes further by charging when a defined business result occurs, such as costs saved or revenue recovered, turning a software license into a business case where the customer pays only when the product delivers results. According to ZoomInfo CEO Henry Schuck, after speaking to hundreds of consultants and customers, nobody really knows where B2B pricing will ultimately land, and the answer changes weekly.
The report explains that AI agents break traditional seat pricing because seats count logins, and agents accomplish work with fewer of them, meaning a vendor charging per seat earns less precisely as its own product becomes more efficient. When a finance team closes its books in two days instead of ten, or a support team resolves most tickets without human intervention, the work needs fewer logins. Large SaaS companies struggle to abandon seat pricing because their entire operations are wired around it: billing counts seats, salespeople earn commissions on contract value booked upfront, forecasts assume smooth recurring revenue, and customer success teams are judged on renewals. The report notes that changing to resolution-based or outcome-based pricing would require turning the business upside down all at once, which explains why many announced pricing changes end up as AI add-ons sold on top of the same seat contract.
For B2B startups, the report recommends starting by naming the one main countable thing the product does that a customer would pay for on its own, and if the founder can name that unit, it becomes the pricing anchor, while inability to name one points toward usage-based pricing. Before signing the first customer, founders should write down the definition of that unit and track what one unit costs to deliver from day one, because without that data, a per-resolution price can win deals that lose money. The report advises testing with a small group first, expecting smaller initial contracts, and deciding early who owns revenue recognition since variable revenue gets uncomfortable in audits. Since 29% of companies in the survey already let customers choose between several models, startups don't have to pick one pricing approach forever, and pricing should be treated as part of the product itself. For incumbents wired around legacy models, this flexibility represents an advantage they may never possess.