Initial AI market skepticism was based on a SaaS model of selling limited-value subscriptions ('seats'). The new reality is a utility model based on consumption ('tokens'). In an agentic era, a single user can drive thousands of dollars in token usage, creating a virtually uncapped revenue stream that justifies massive infrastructure investment.

Unlike traditional SaaS, AI companies have significant variable costs for compute and tokens. This makes revenue a poor proxy for profitability, as their gross margins are fundamentally different from high-margin software businesses—a fact many investors miss.

Sridhar Ramaswamy suggests software valuation multiples are contracting because investors see through the strategy of just adding an 'AI SKU.' The market believes this approach won't win, favoring integrated, consumption-based models where customers only pay for demonstrated value from AI.

The ARR/SaaS model, built on predictable human usage, is failing. AI agents can consume resources worth thousands of dollars for a low subscription fee, breaking the unit economics. This forces a shift to metered, consumption-based pricing similar to utilities like electricity.

Current AI pricing models, which pass on expensive LLM costs to users, are temporary. As LLM costs inevitably collapse and become commoditized, the winning companies will be those who have already evolved their monetization to be based on the value their product delivers.

AI is making core software functionality nearly free, creating an existential crisis for traditional SaaS companies. The old model of 90%+ gross margins is disappearing. The future will be dominated by a few large AI players with lower margins, alongside a strategic shift towards monetizing high-value services.

Unlike high-margin SaaS, AI agents operate on thin 30-40% gross margins. This financial reality makes traditional seat-based pricing obsolete. To build a viable business, companies must create new systems to capture more revenue and manage agent costs effectively, ensuring profitability and growth from day one.

The traditional per-seat SaaS model is becoming a "tax on productivity" in an agent-driven world. As companies buy agents to do work instead of software for humans, the model shifts. Sam Altman's comment that every company is now an API company reflects this move from user-based pricing to value-based, programmatic access.

Sierra CEO Bret Taylor argues that transitioning from per-seat software licensing to value-based AI agents is a business model disruption, not just a technological one. Public companies struggle to navigate this shift as it creates a 'trough of despair' in quarterly earnings, threatening their core revenue before the new model matures.