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.

Seat-based and token-based pricing for AI are intermediate steps. The ultimate model is outcome-based, where customers pay for specific value delivered—like a successful investment idea or a completed report. This perfectly aligns vendor cost with customer value, bypassing debates over token consumption ROI.

A powerful software value-creation lever is "engineering out" partners. By acquiring or building technology that replaces a licensed third-party service, a company eliminates a variable cost. In SaaS, this cost reduction applies retroactively to the entire customer base, dramatically boosting gross margin.

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.

AI tools aren't just making employees more efficient; they are replacing human labor. This allows software companies to move from cheap per-seat pricing to a new model based on outcomes, like charging per support ticket resolved, capturing a much larger share of the value.

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.

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.