Innovation Policy and AI-Enabled Transformation

Artificial intelligence has moved from a specialist computational field into a general organisational, industrial and political question. It reshapes production, coordination, learning, and competition, while also unsettling the conceptual boundaries that have long separated innovation policy from business model analysis. This chapter argues that AI-enabled transformation should be understood through a combined lens that links mission-oriented innovation policy, dynamic capabilities, and business model change. The key claim is straightforward. AI does not matter only because it automates tasks or improves prediction. It matters because it reorganises how firms sense opportunities, create and distribute value, capture returns, and position themselves within wider ecosystems. At the same time, it reopens a foundational policy question about direction. If AI is treated as a neutral productivity tool, policy remains trapped within a narrow market-failure logic. If AI is treated as an infrastructural and strategic technology, policy must confront the harder issues of purpose, capability, coordination, and public value. Building on the arguments of mission-oriented innovation policy and the literature on digital transformation of business models, this chapter develops a critical review of how AI changes firms and how policy should respond. It argues for a framework in which public institutions shape directions of change, crowd in experimentation, discipline concentration, and build the collective capabilities required for broad-based adoption. The chapter concludes that effective AI transformation depends less on diffusion alone and more on the alignment between public missions, organisational capabilities, business model redesign, and democratic governance.