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Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings. This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled-"smart"-systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work-by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers. These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time, allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy, a robotic assistant for fast food preparation. For each one, Davenport and Miller describe in detail the work context for the system, interviewing job incumbents, managers, and technology vendors. Short "insight" chapters draw out common themes and consider the implications of human collaboration with smart systems.

A clear-eyed look at how AI can complement (rather than eliminate) human jobs, with real-world examples from companies that range from Netflix to Walmart. Descriptions of AI's possible effects on businesses and their employees cycle between utopian hype and alarmist doomsaying. This book from MIT Sloan Management Review avoids both these extremes, providing instead a clear-eyed look at how AI can complement (rather than eliminate) human jobs, with real-world examples from companies that range from Netflix to Walmart. The contributors show that organizations can create business value with AI by cooperating with it rather than relinquishing control to it. The smartest companies know that they don't need AI that mimics humans because they already have access to resources with human capability--actual humans. The book acknowledges the prominent role of such leading technology companies as Facebook, Apple, Amazon, Netflix, and Google in applying AI to their businesses, but it goes beyond the FAANG cohort to look at AI applications in many nontechnology companies, including DHL and Fidelity. The chapters address such topics as retraining workers (who may be more ready for change than their companies are); the importance of motivated and knowledgeable leaders; the danger that AI will entrench less-than-ideal legacy processes; ways that AI could promote gender equality and diversity; AI and the global loneliness epidemic; and the benefits of robot-human collaboration. Contributors Cynthia M. Beath, Megan Beck, Joe Biron, Erik Brynjolfsson, Jacques Bughin, Rumman Chowdhury, Paul R. Daugherty, Thomas H. Davenport, Chris DeBrusk, Berkeley J. Dietvorst, Janet Foutty, James R. Freeland, R. Edward Freeman, Julian Friedland, Lynda Gratton, Francis Hintermann, Vivek Katyal, David Kiron, Frieda Klotz, Jonathan Lang, Barry Libert, Paul Michelman, Daniel Rock, Sam Ransbotham, Jeanne W. Ross, Eva Sage-Gavin, Chad Syverson, Monideepa Tarafdar, Gregory Unruh, Madhu Vazirani, H. James Wilson

Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today's Financial Services Industry · The future state of financial services and capital markets - what's next for the real-world implementation of AITech? · The innovating customer - users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the 'unbundled corporation' & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important