As AI moves from being a simple tool to an autonomous agent, pricing models are evolving. Companies like Sierra, chaired by OpenAI's Brett Taylor, advocate for outcome-based pricing, which charges for delivered results (e.g., a completed report) rather than the underlying token consumption.

AI enables a fundamental shift in business models away from selling access (per seat) or usage (per token) towards selling results. For example, customer support AI will be priced per resolved ticket. This outcome-based model will become the standard as AI's capabilities for completing specific, measurable tasks improve.

Bret Taylor's firm, Sierra, is pioneering an "outcomes-based pricing" model for its AI agents. Instead of charging for software usage, they only charge clients when the AI successfully resolves a customer's problem without human escalation. This aligns vendor incentives with tangible business results like problem resolution and customer satisfaction.

HubSpot's shift to 'outcome-based' pricing for AI, charging per 'resolved conversation,' introduces complexity. Customers now face budget uncertainty and must rely on HubSpot's definition of a successful outcome, which may not align with their own business value, creating more questions than answers.

The most logical pricing model for AI is to benchmark it against the human labor costs it displaces. While a PR challenge for legacy companies, AI-native firms will likely adopt this outcome-based model because it is more tangible for finance leaders than abstract, unpredictable credit systems.

AI startups should choose their pricing model based on a 2x2 matrix of autonomy (human-in-the-loop vs. fully automated) and attribution (how clearly its value can be measured). Low levels lead to seat-based pricing, while high levels of both unlock outcome-based models.

AI is splitting software into two categories: "access products" and "work products." While access tools can stick with seat-based pricing, work products (e.g., AI that processes legal contracts) must adopt outcome-based pricing, as value is tied to output, not the number of users.

OpenAI Chair Bret Taylor argues that the biggest hurdle for established software companies isn't adopting AI technology, but disrupting their own business models. Moving from per-seat licenses to the outcome-based pricing that agents enable is a more profound and difficult challenge.

The B2B software business model is evolving from licenses and subscriptions toward outcome-based pricing, where customers pay for successful task completion. While currently limited to measurable areas like customer support, this model represents the next major disruptive wave as AI makes more outcomes quantifiable.