Industries with historically low software adoption (like trial law or dentistry) are now viable markets. Instead of selling a tool, AI startups are selling an outcome—the automation of a specific labor role. This shifts the value proposition from a software expense to a direct labor cost replacement.

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.

While fee-for-service models incentivize in-clinic treatments, value-based care shifts the focus to outcomes and overall cost. Under these new models, home dialysis—which offers better patient outcomes and lower societal costs—becomes more profitable for providers, creating a powerful financial incentive to drive adoption.

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.

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 current moment is ripe for building new horizontal software giants due to three converging paradigm shifts: a move to outcome-based pricing, AI completing end-to-end tasks as the new unit of value, and a shift from structured schemas to dynamic, unstructured data models.

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.

During the pandemic, companies adopted digital health solutions to make employees happy. Now, the focus has returned to fundamentals. Buyers demand solutions that demonstrably reduce costs, like insurance claims or sickness absenteeism, rather than just offering 'added value' perks.

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.