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Bret Taylor of Sierra argues outcome-based pricing (charging for a resolved case) is superior to usage-based pricing (charging for tokens). It aligns vendor and customer interests by tying cost directly to business value, not resource consumption. This forces the vendor to improve product effectiveness, not just optimize for usage.

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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.

In categories like customer support, where AI can handle the vast majority of queries, charging per human agent ('per seat') no longer makes sense. The business model is shifting to be outcome-based, where customers pay for the value delivered, such as per ticket resolved or per successful interaction.

Standard SaaS pricing fails for agentic products because high usage becomes a cost center. Avoid the trap of profiting from non-use. Instead, implement a hybrid model with a fixed base and usage-based overages, or, ideally, tie pricing directly to measurable outcomes generated by the AI.

The dominant per-user-per-month SaaS business model is becoming obsolete for AI-native companies. The new standard is consumption or outcome-based pricing. Customers will pay for the specific task an AI completes or the value it generates, not for a seat license, fundamentally changing how software is sold.

The traditional per-seat SaaS model is losing relevance. As AI allows for the completion of discrete workflows, customers expect to pay for the outcome ('do this thing for me'), not for access. This per-task model is a significant competitive advantage against legacy players.

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.

The next major business model shift in software is from seat-based pricing to outcome-based pricing (e.g., paying per task completed). This favors AI-native newcomers, as incumbents will struggle to adapt their GTM and financial models.

In the age of AI, software is shifting from a tool that assists humans to an agent that completes tasks. The pricing model should reflect this. Instead of a subscription for access (a license), charge for the value created when the AI successfully achieves a business outcome.

Intercom priced its AI agent per successful resolution, aligning its incentives with customers. Though initially losing money on each resolution ($1.21 cost vs 99¢ price), efficiency gains made it profitable, proving outcome-based pricing can succeed for AI products.