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 17 starts with a discussion of an AI-first strategy. The central goal of a business with an AI-first strategy is to maximize prediction accuracy even if that compromises other goals. AI can be disruptive to established firms since they have weaker economic incentives to use the technology than startups do, but those same firms may have a hard time catching up once competitors get ahead in the training and use of AI tools. The timing of when to start using AI tools is another strategic decision; they're typically trained in house, but they learn faster when deployed into commercial use. The benefits of faster learning must be weighed against the risks of releasing a product before it's ready.