OpenAI Chief Financial Officer Sarah Friar has outlined a vision for the company’s future revenue models that goes beyond traditional subscriptions, proposing innovative licensing structures tied to customer outcomes. Speaking on a recent podcast, Friar discussed the potential for OpenAI to earn royalties when its AI technologies help clients achieve measurable results—such as a pharmaceutical company launching a successful drug developed with the help of OpenAI’s tools. In this model, OpenAI could receive a percentage of sales from a breakthrough medicine, aligning the company’s financial success with that of its partners. Friar framed this as a way to create shared incentives, where OpenAI profits only when its customers succeed. She described this evolving strategy using a metaphor: the Rubik’s Cube. “One of the things I love about a Rubik’s Cube,” she said, “I’m probably not getting the number exactly right, but I think it has 43 quintillion different states it can be in.” She likened OpenAI’s current landscape to a constantly shifting cube, where each twist represents a strategic decision—whether in technology, partnerships, or monetization. When OpenAI launched, it operated like a single block in the cube: one cloud provider (Microsoft), one chip partner (Nvidia), one flagship product (ChatGPT for consumers), and one subscription model. Today, the company has diversified across multiple cloud providers, chip suppliers, and product lines—including Sora, enterprise tools, industry-specific AI solutions, and research platforms. This complexity has also transformed its business model. While it began with a simple consumer subscription to cover compute costs, OpenAI now offers tiered pricing, software-as-a-service models, and credit-based systems for high-end applications. Friar said the company is now exploring additional revenue streams, including commerce, advertising, and outcome-based licensing. The Rubik’s Cube metaphor, she explained, illustrates how OpenAI can combine technical choices—like low-latency chips—with premium services to justify higher pricing, or prioritize scale to attract millions of free users and build a foundation for ad-driven revenue. Yet a key constraint remains: compute capacity. Friar emphasized that demand for OpenAI’s services is not limited by interest, but by available computing power. This reality, she said, makes diversifying revenue models not just strategic, but essential. “You can start to see how the goal in the last 12 months has been creating more and more strategic options that allow me to keep paying for the compute we need to really achieve our mission,” she added. As OpenAI continues to expand its technical and commercial footprint, Friar’s vision points to a future where the company’s financial success is deeply intertwined with the real-world impact of its AI systems.