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.

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.

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.

Professional services firms on a billable hour model face an existential threat from AI. As AI compresses work from hours to minutes, clients will demand savings, forcing firms to transition to defensible, value-based pricing models or risk obsolescence.

AI tools drastically reduce the time needed to complete complex tasks, breaking the traditional billable-hour model for consultants and agencies. The focus must shift to value-based pricing, where compensation is tied to the problem solved or the output created, not the hours worked.

While foundational models are metered by tokens, vertical AI solutions in specific domains like healthcare or finance will increasingly compete by charging for measurable business outcomes. Customers will hold these apps accountable for delivering tangible ROI, making outcome-based pricing a key differentiator.

The consulting giant is shifting its business model from pure advisory work (fee-for-service) to an outcomes-based approach. McKinsey co-creates a business case with the client and contractually underwrites the results, aligning its incentives directly with client success.

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.