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Section 1. Understanding AI and machine learning: The business of artificial intelligence: what it can -- and cannot -- do for your organization / Erik Brynjolfsson and Andrew McAfee -- Inside facebook's AI workshop: at the social network behemoth, machine learning has become a platform for the platform, an interview with Joaquin Candela by Scott Berinato -- Why companies that wait to adopt AI may never catch up: the "fast follower" strategy won't work / Vikram Mahidhar and Thomas H. Davenport -- Section 2. Adopting AI: 3 questions about AI that nontechnical employees should be able to answer: how does it work, what is it good at, and what should it never do? / Emma Martinho-Truswell -- Is your company's data actually valuable in the AI era?: the problem with "data is the new oil." / Ajay Agrwawal, Joshua Gans, and Avi Goldfarb -- How to choose your first AI project: pick a quick win to build internal support / Andrew Ng -- How Harley-Davidson used artificial intelligence to increase New York sales leads by 2,930%: and it led to more revenue and more jobs / Brad Power -- What will happen when your company's algorithms go wrong?: you need to have a plan / Roman V. Yampolskiy -- Section 3. AI and the future of work: How will AI change work?: here are 5 schools of thought: in some versions, society will fundamentally change / Mark Knickrehm -- Collaborative intelligence: humans and AI are joining forces: humans and machines can enhance each other's strengths / H. James Wilson and Paul Daugherty -- Section 4. The future of AI: 3 ways AI is getting more emotional: as we spend more time with our devices, we emit more data to be analyzed / Sophie Kleber -- How AI will change strategy: a thought experiment: E-commerce could move from shopping-then-shipping to shipping-then-shopping / Ajay Agrwawal, Joshua Gans, and Avi Goldfarb -- The future of AI will be about less data, not more: we need computers with some common sense / H. James Wilson, Paul Daugherty, and Chase Davenport.
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