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.

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.

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.

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.

As AI agents become the primary "users" of sophisticated software, the traditional per-seat licensing model becomes obsolete. Pricing will inevitably shift to a value-based model, tied to outcomes the AI delivers—such as cycle reduction or performance gains—rather than human operators.

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.

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.

AI is moving beyond enhancing worker productivity to completing entire projects, like drug discovery or engineering designs. This shift means software will be priced like a services business, based on the value of the outcome delivered, not the number of users with access.

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.