In "Prediction Machines," economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explore the advancement and growing use of artificial intelligence (AI). The key to AI is not actually intelligence but prediction. This text looks at the value of prediction and data, the importance of trade-offs, and the impact of AI in the workplace. Beneficial to business leaders, financial analysts, policy makers, and students, "Prediction Machines" offers insights, tools, and strategies on how to adapt businesses to the world's ever-growing use of AI. Part 4, comprising chapters 15 to 18, looks at various strategies for implementing AI in business models. Topics include strategies for those in leadership positions, how AI can transform organizations, AI-first strategies, and managing AI risk. Chapter 16 explores how businesses can change by implementing AI. Where one business ends and another begins needs to be determined, and prediction machines can reduce the uncertainty that influences this choice. By reducing uncertainty, they can increase the ability to write contracts, which then increases incentive for businesses to contract out capital equipment and labor but decreases incentive to contract out labor that specifically focuses on judgment. AI will also increase incentive to own data; contracting out for data may be necessary at times.