Intense demand for AI tokens is outstripping compute supply, making flat-rate SaaS pricing unsustainable. Companies like GitHub are now shifting to usage-based billing to cover escalating inference costs, marking a fundamental change in how AI products are sold and signaling a broader industry trend.

As more companies integrate AI, their costs are tied to variable usage (e.g., tokens, inference). This is causing a profound, economy-wide transformation away from predictable seat-based subscriptions towards more dynamic usage-based models to align costs with revenue.

AI development isn't free; it shifts the economic model of software from zero marginal cost to one with variable costs based on token consumption. This makes Cost of Goods Sold (COGS) a critical, and often new, metric for SaaS founders.

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.

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 shift to agentic AI means costs are no longer predictable per-seat subscriptions but variable expenses based on usage (tokens, compute). This requires managing AI like a capital allocation or a new form of labor, not just another software tool, a reality that early adopters are now grappling with.

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 business model for AI is pivoting away from SaaS-style subscriptions. Enterprise-focused labs like Anthropic see massive revenue not from adding users, but from the immense token consumption of API power users. A single developer can be 100x more valuable than a subscriber, forcing a shift to consumption-based pricing.

A few months ago, the fear was AI replacing SaaS businesses. Now, the pressing issue is managing massive AI bills. This has elevated 'token economics'—optimizing costs by using different models for different tasks (model routing)—from an advanced technique to a non-negotiable, table-stakes practice for any serious AI implementation.