Stripe leverages domain-specific foundation models and real-time payment embeddings to detect sophisticated fraud, improving detection rates from 59% to 97% for large users. The company addresses emerging challenges in the AI economy, such as free trial and refund abuse, by offering tailored fraud prevention tools. It supports AI startups with flexible billing models, including token-based and outcome-driven pricing, while reducing costs through stablecoin adoption. The Agentic Commerce Protocol, launched with OpenAI, establishes a standardized way for AI agents to conduct transactions, already adopted by major retailers. Internally, Stripe uses LLMs to accelerate product development and streamline operations, though measuring long-term ROI remains complex. The platform also enables non-technical founders via low-code tooling and sandbox environments. Despite rapid growth in AI companies—evidenced by faster revenue scaling and global reach—challenges around churn and economic measurement persist. Emily argues that AI’s impact on GDP may lag but will ultimately expand consumption by automating routine tasks, especially for high-income users. Brand, design, and trust remain crucial differentiators in an AI-driven world.