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The AI Advantage: How to Put the Artificial Intelligence Revolution to Work (Management on the Cutting Edge)

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Review

An essential guide to business.―ForbesDavenport reports on what AI has accomplished so far, where it has failed, and where it might soon spectacularly succeed...He explains the different types of tech that commonly fall under the AI umbrella, explores the ways businesses are incorporating AI into their processes, and examines the ethical considerations of this powerful new technology.―BizEd

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AI is real, but not easy. Here, Tom Davenport approaches this difficult topic with his trademark explanation, insight, and real-world examples. And the book's title is perfect: you'll get access to the biggest source of competitive advantage today if you read The AI Advantage.―Andrew McAfee, Principal Research Scientist at MIT and coauthor of The Second Machine Age and Machine | Platform | CrowdConsider this book as your 'AI myth buster'―a fabulous guide to anyone faced with vendor hype and moonshot expectations of AI. It cuts through the clutter, giving a clear explanation of the true capabilities of AI, a pragmatic approach of how to think through its potential in your organization, and methods to drive the effective adoption of AI at scale. A must-read!―Dave Gledhill, Group CIO, DBS BankAI pervasiveness is inevitable. It will be everywhere, grow hyperbolically, and catch most by surprise. The only question is when that tipping point will be. Davenport's book provides a holistic path to prepare organizations and individuals for what is to come in a structured manner full of real-life examples and applications.―Leandro DalleMule, Head of Information Management and Chief Data Officer, General Insurance, AIGOrganizations are looking to learn about the practical applications and business impact of AI. Many of their questions will be answered by this excellent book.―Janet Foutty, Chair and CEO, Deloitte Consulting, LLPThe AI Advantageis a must-read for executives who wish to truly become cognitive corporationleaders and not merely 'cocktail party' pontificators who dupe their colleagues into believing they've 'got AI,' but, in actuality, only have a few pilots possessing little to no business impact at all.―A. Charles Thomas, Global Chief Data and Analytics Officer, General MotorsThe promise of AI technology is to transform us. But things get in the way: hype, denial, and just simple misunderstanding. Once again, Tom Davenport has taken on the role of the business sherpa, guiding decision makers through the maze of technology to the business transformation we all want.―Kristian J. Hammond, Professor of Computer Science, Northwestern University; and Chief Scientist, Narrative Science

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Product details

Series: Management on the Cutting Edge

Hardcover: 248 pages

Publisher: The MIT Press; 1 edition (October 16, 2018)

Language: English

ISBN-10: 0262039176

ISBN-13: 978-0262039178

Product Dimensions:

6 x 0.9 x 9 inches

Shipping Weight: 1.1 pounds (View shipping rates and policies)

Average Customer Review:

5.0 out of 5 stars

6 customer reviews

Amazon Best Sellers Rank:

#180,629 in Books (See Top 100 in Books)

I have known Tom for many years and enjoyed his books - and this one is another good one. Tom does his usual excellent job of introducing a technical topic - AI and machine learning - and focusing on what business leaders need to know about it. While he has a chapter on the various approaches to adopting AI technology, the book's key message is that a technology-first approach to AI is a bad idea. Instead of technology-led "moonshots", enterprises should use AI to solve practical, immediate, operational problems.The book begins with a discussion of the role of AI in the enterprise and surveys what companies are doing today – both successes and failures. It was particularly refreshing to see failures discussed and Tom does a nice job of using some of these failures to illustrate how best to approach AI. He believes AI is going to transform companies, albeit perhaps more slowly than some believe, and encourages companies to identify a coherent AI strategy. He provides some good material on the elements of an AI strategy and outlines how different companies might take different approaches. Usefully for business executives, he provides a very accessible survey of the capabilities of AI and how they might reasonably be used, not in the future but now – discussing in passing how work is likely to need to be redesigned to take full advantage of these technologies.In later chapters he talks about jobs and skills in a world where AI is increasingly pervasive and about some of the social and ethical issues such as transparency and bias.This is not a book that is going to add to your technical knowledge about AI but its a great book for business executives and for those who want to think more deeply about how AI will change their business.

Imagine the fortunate CEO of a large established enterprise that is lucky enough to sit next to Tom Davenport on a transpacific flight. This CEO was perhaps already wondering what her firm should be doing about AI. And here sits the nicest, most honest and straightforward guy on the planet, who knows more about this topic than anyone, right in the next seat. What a break! She asks all the right questions, and gets Davenport's deeply informed and beautifully expressed and explained answers:• What is AI good for right now? Improving your operations.• Should we be trying to use AI to improve operations? Absolutely yes, you should.• Is all the hype real? No, but that's not important -- what is important is starting to experiment and learn the facts behind the hype.• Am I already too late? No!• What kinds of things are companies doing with AI? Well... (The answer to this question extends over cocktails and dinner, but the range of examples makes you certain that Davenport knows what he's talking about.)• OK, I'm persuaded. Where to begin? Make some key strategic decisions: What data are you going to exploit, what AI talent do you need, and will you buy that talent, build it or rent it.• So, should I be thinking about what kind of AI to master? NO, look at it the other way around: Try to figure out which of your business processes AI is likely to seriously disrupt. (Many examples make this very clear.)• Will we be laying off a lot of people? In the short run, probably not, BUT even in the short run you could be changing what a lot of people do and the skills people need. In the long run, some job loss is possible; dramatic skill changes are far more certain.• (A pause while our CEO gets a little sleep as Davenport explains, very clearly and insightfully, alternative technology and data strategies for AI. It's a pity her MBA program didn't include a course on IT.)• How can we avoid AI ethical pitfalls? Don't continue to be dumb about AI. Give this book to every manager in your company. If they are smarter about AI, they'll be less likely to stumble into a pit.

In the first chapter and throughout the narrative of his latest book, Tom Davenport provides information and insights about several of the most promising cognitive technologies: statistical machine learning, neural networks, deep learning, natural language processing (NLP), rules-based expert systems, physical robots, and robotic process automation (RPA). His primary purpose is to provide an honest and straightforward look at the impact [these powerful technologies] will have on businesses over the short and long term."These are among the passages of greatest interest and value to me, in Chapters 1-5, also listed to suggest the scope of Davenport's coverage:o What Do We Mean by AI/Cognitive Technologies? (Pages 9-11)o The Broad Rationale for Cognitive Technology in Business (24-25)o Many Industries, Many Functions (27-30)o What's Still Hard for Companies (34-37)o An Overview of the Cognitive Project Landscape (39-41)o Three Types of AI Capabilities (41-45)o Building on Current Analytical Strengths (50-51)o Engaging in Cognitive Work Design (55-57)o The Future Cognitive Company (58-59)o The Strategic Impact of Cognitive Technologies, and, Internal or External Object8ves? (63-65 and 66-69)o Why Existing Business Models Persist in the Face of AI (80-83)o Content and Talent Strategies (85-91)o Country-Based AI Strategies Create (94-96)o Highly Granular Prediction and Classification Models (100-102)o Organizational Implications of Process Applications (103-104)o Plan and Optimize Operations(113-114)o Perceive and Recognize Images (115-116)o Challenges to Broad Implementation of Image Recognition (118-119)o Vehicles Organizational Implications of Fully Autonomous Vehicles (121-122)o The Need for Process Architecture or (Re)Engineering (126-128)In Chapter 6, Davenport shares his thoughts about jobs and skills in a world of smart machines. He suggests that augmentation -- smart humans working in smart collaboration with smart machines -- is by far more likely to have wider and deeper impact than will large-scale automation is. Why? He offers five reasons:"First, as some of the automation research cited suggests, AI tends to support or automate tasks, not entire jobs ...A second reason augmentation is more likely is that surveys suggest that most managers neither want nor expect large-scale automation...A third factor automation is less likely than augmentation is that people find new jobs and tasks to perform when previous tasks are taken over by automation...A fifth and final reason massive job loss is not a concern is that a lot of entirely new jobs will be created." All this is explained in much greater detail on Pages 133-137.Today, many workers fear that machines will be taking their jobs. Scribes certainly worried about that after they heard about the printing press, and others later also worried about steam powered transportation, the McCormick reaper, mass production assembly lines, the telephone, the internet, and wireless electronics. Over the decades, machines have out-produced humans and at a fraction of the cost of their labor.In months and years to come, there will be no shortage of jobs for those who can collaborate productively and profitably with machines. They will have a competitive advantage, an AI Advantage.These are among Thomas Davenport's concluding thoughts: "Just as the late 1990s and early 2000s heralded the age of the internet, the time for AI in the enterprise is here. If your company's direct competitors aren't already embracing it, disruptive startups will." Employing AI "and learning through experimentation and experience will mean that companies can benefit enormously from some of the most exciting and powerful technologies ever created by human beings."Ready to embrace AI and put it to work in your organization? If so, almost everything you need to know is provided in this book.

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The AI Advantage: How to Put the Artificial Intelligence Revolution to Work (Management on the Cutting Edge) PDF