Everyone is building AI into their products. Far fewer are asking whether those products will actually create commercial value. An AI feature can delight customers - and still hurt your margins. It can drive adoption - without creating willingness to pay. It can solve a real customer problem - and still have the wrong pricing model. And sometimes, the very thing that makes an AI product valuable changes how the product should be packaged and monetized. These are increasingly product decisions, not questions to hand off to Finance or GTM after the product has already been built. So what should product leaders be thinking about before they commit to the next AI bet? In this session, we’ll explore the decisions behind commercially successful AI products: how customer value connects to willingness to pay, how the nature of an AI product changes its pricing and packaging options, why AI economics can challenge familiar SaaS assumptions, and what product leaders should validate while they still have the ability to change the product. Because in the age of AI, the question isn't just: can we build something customers want? It's whether we can turn that value into a product customers will pay for - and a business that benefits when they use it.