The AI Advantage: How to Put the Artificial Intelligence Revolution to Work
Thomas H. Davenport
MIT Press (October 2018)
Charting “the path of artificial intelligence and cognitive technologies in mainstream businesses”
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.