The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable

by Seth Earley, Thomas H. Davenport (Foreword)

Learn how to develop and employ an ontology , the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence—AI—is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave—rather than be crushed by it—need to read The AI-Powered Enterprise . The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development.

Genres: Technology, Business

320 pages, Hardcover

Published April 28, 2020

Reviews

[Marcus Österberg]

Unsurprisingly Seth argues that you cannot have AI without good information architecture. A lesson most leaders still need to learn unfortunately.

[Ben · Rating 4 out of 5]

Power Up Your Business

This was a great book on utilizing state-of-the-art technology to become a more productive business.

I enjoyed the concepts in this book, and would recommend it for those in businesses that harness information technology.

I found it beneficial for my own career.

3.8/5

[Jay · Rating 1 out of 5]

I was looking into ways of using controlled terminologies and ontologies to assist in governing LLM output, and this book was recommended by a speaker at AMIA. The session did not go into any details, so I bought the book, looking forward to a bit more detail in how to integrate these two powerful but fundamentally different technologies.

This is not that book. It is a business book, which I mean in the bad way. A consultant catalogs all the platitudes and bromides about how what he does will transform your business without a single concrete example, and includes contact information in case you'd like to hire his firm. There are stories, of course, about providing value to blue chip clients, but not a whimper about what might actually be involved in yoking these two beasts together.

The one useful bit: the analogy of the chart of accounts. You can ask the LLM to come up with whatever inspired and broadly informed answer it can provide about a financial question, but the answer has to fit in the chart of accounts. You can't just train it on the chart because its behavior remains stochastic, and you don't know what might pop up that trumps the human-curated chart. That last sentence, by the way, is me: you'll find nothing that specific in this book.

If you know what you want to do and you need a marketing brochure to show an executive, this might be the thing. Otherwise, it's not.

[Anthony · Rating 4 out of 5]

Was a good book for the specific niche I work in - if it wasn't so relevant it would have had 3 stars. But it was very helpful. Could have been 100 pages shorter.

[Meredith · Rating 2 out of 5]

Basically one long sales pitch for utilizing Earley's company. If you're interested in cutting edge approaches and use cases to leveraging ontologies consider looking elsewhere.