This chapter covers
- Why almost any product can be enhanced with AI
- How AI-driven products differ from “traditional” software
- How AI projects often go wrong
- The mental model for AI systems
- The skill set of an AI product builder
Let’s start with a bold statement: if your business offers digital products or services, AI can enhance or even completely transform it. AI can refine marketing strategies based on customer data and automate routine customer support tasks. AI can extend existing products with new features such as smart search and agentic chatbots. AI can even be the foundation of new, disruptive products such as Vercel’s v0.dev, which allows you to build and deploy apps at unprecedented speed. AI is here, and businesses that integrate it effectively have a competitive edge.
As always, getting these benefits requires changes to the strategies, tools, and processes you use to develop and manage these products. AI introduces new challenges in product development, from handling imperfect data to managing unpredictable outputs. Many initiatives fail—not for lack of potential but because teams lack the expertise and frameworks to create these products effectively. Common pitfalls include unclear value propositions, poor data quality, unrealistic expectations, and underestimating the effort required for customization.