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 3, consisting of chapters 12 through 14, explores AI tools, how to implement them into the workforce, and how that implementation may change the nature of certain jobs and bring about new ones. Chapter 13 discusses the process of decomposing tasks to see where prediction machines can be implemented. This process allows for an estimation of the costs and benefits of the enhanced prediction. The AI canvas is given as a tool to help with decomposition; it focuses on the three types of required data: training, input, and feedback. The AI canvas is also centered around prediction, which forces companies to identify the core prediction of the task.