Organizations are investing heavily in data and AI, yet few can clearly show the return on that investment. The new challenge is not only how to turn data into a product, but how to attach commercial value to AI models, agents, and capabilities that rely on that data.

Whether your monetization goal is internal ROI (productivity gains, automation value, AI-driven efficiency) or external commercialization (data and AI products, APIs, insights-as-a-service), it comes down to the same principle: putting a price on intelligence.

• Explore how to identify and prioritize data and AI assets with real commercial potential.

• Learn how to price, build, and scale data and AI products effectively.

• Discover what governance, trust, and cost transparency frameworks are needed to sustain commercialization.

Challenge assumptions, share practical examples from across industries, and co-create strategies that turn data and AI from a sunk cost into a sustainable commercial engine.