The AI Advantage: How to Put the Artificial Intelligence Revolution to Work by Tom Davenport. Tom has written several well respected books. Reading Competing on Analytics in 2008, provides me stellar view of business metrics. Keeping Up with the Quants and Big Data at Work both reveal deep insights every organization must absorb to understand predictive analytics and big data. Surprisingly, the AI Advantage falls flat by comparison.
The book’s pitch is well researched, yet there is a surprising lack of unique cases compared to his three books above. Likewise, the opening chapter “Artificial Intelligence Comes of Age—Slowly” provides a general overview to IBM’s Watson. Small hits, and yet a larger unfocused ability of Watson to move the needle on cancer research.
The promise of AI’s subset, machine learning (ML) is very over-promoted across today’s IT sales marketplace. The opening chapter reveals some deep AI shortcomings that should not be ignored.
Meanwhile, examples throughout the book refer to the Robotic Process Automation (RPA), a somewhat flavor of machine learning. Likewise, this extends into Chapter 2: AI in the Enterprise, the impact of AI for knowledge workers. This type of technology advance is impacting a cognitive advantage in healthcare.
Surprisingly, The AI Advantage released in 2018. But the role of AI driven Deep Fakes is missing. Launched in 2014, Generative Adversarial Network (GAN) technology may indeed be the most contested application of ML.
While amusing for movies and celebrities, certainly there are significant impacts upon society regarding government, corporations, and foreign relations. Shockingly the manipulation of voice has already resulted in financial transfers to criminal organizations.
However, call center and chat bot technology leveraging AI is the book’s most viable market solution. But there is disappointment if a reader is looking for substantial solutions.
Davenport shares repeated failures of Facebook’s rapid adoption of AI. Likewise, this includes marketing based upon facial recognition to the 2016 election. On the other hand, The AI Advantage shares business cases of AI applications outside of Google, Facebook, and Amazon. Moreover, lessons by insurance firms State Farm, Allstate, Geico, and Progressive prove intriguing. There is a brief position of AI ethics is scattered throughout.
In conclusion, The AI Advantage lacks substance of Tom’s previous, respected books above. Competing on Analytics offered a maturity matrix for adopting analytics across the enterprise. AI Advantage is missing an equivalent. This offers some practical directions for larger enterprise organizations.
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