For many AI companies, the primary growth lever is no longer advertising spend but offering free trials and credits. This makes their CAC directly tied to expensive compute resources, elevating the financial impact of trial abuse from a nuisance to a major business risk.

Because compute theft occurs before a transaction, fraud risk for AI companies starts at sign-up, not checkout. In response, Stripe has adapted its Radar product to be integrated at the beginning of the user lifecycle, assessing risk before any costly credits are granted.

The accessible AI software that helps brands quickly build websites, create ads, and list products is a double-edged sword. These same tools are exploited by fraudsters to accelerate the speed and scale of their nefarious activities, creating an arms race where brands must also adopt AI to defend themselves effectively.

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.

An AI agent cannot simply use a human's credentials. It requires its own identity, permissions, and access controls for security and traceability. This means SaaS companies will likely charge for agent seats, creating a significant new revenue stream.

The current subsidized AI subscription model is unsustainable. The inevitable shift to pay-per-token pricing will expose the true cost of inference. For tasks like coding, where AI can "hallucinate" and burn tokens in loops, this creates unpredictable and potentially exorbitant costs, akin to gambling.

The "bill at the end of the month" model for AI token usage creates significant credit risk from fraudulent accounts. By enabling real-time, per-token payments with stablecoins, companies can offer self-serve access without worrying about users racking up large bills and disappearing.

Unlike SaaS where marginal costs are near-zero, AI companies face high inference costs. Abuse of free trials or refunds by non-paying users ("friendly fraud") directly threatens unit economics, forcing some founders to choke growth by disabling trials altogether to survive.

Unlike traditional SaaS, AI companies' free tiers have high marginal costs from compute. Fraudsters now steal these valuable compute credits via multi-account and free trial abuse, creating an existential threat to unit economics that goes beyond simple payment fraud.