Source: Harvard Business Review
October 19, 2016
I’m teaching a new course this semester on cognitive technologies (AKA artificial intelligence) to Babson MBAs. Many of them are new to this set of technologies, and seeing the topic through my students’ eyes has made me realize how overwhelming it can be. There are so many different types of AI, each requiring some technical knowledge to fully grasp, that newcomers to the field often have difficulty figuring out how to jump in.
In the simplest case, cognitive technologies can be just more autonomous extensions of traditional analytics — automatically running every possible combination of predictive variables in a regression analysis, for example. More complex types of cognitive technology — neural or deep learning networks, natural language processing, and algorithms — can seem like black boxes even to the data scientists who create them.
Though these technologies can seem daunting, the good news is that getting started with cognitive technologies is getting easier all the time. Many vendors have jumped into the field, and their offerings provide options for any company wanting to make their processes or products smarter. I can think of at least seven ways to begin using cognitive tools, although some are clearly easier (and cheaper) than others. Because implementing these technologies is a key factor in deciding how to move forward, I’ve combined the cognitive entry points into three categories: “Mostly Buy,” “Some Buy, Some Build,” and “Mostly Build.”
I’m sure there are other angles that a company could take to adopting cognitive technology, but to date these seem to be the most common ones. Each has different implications for the kinds of skills an organization needs and how it manages the technology once it comes in the door. Some ambitious organizations may want to pursue multiple entry points at once. It’s great that there are so many options, but when management teams decide to integrate cognitive technology into their strategies, they should think hard about which one they plan to pursue.
Thomas H. Davenport is the president’s distinguished professor in management and information technology at Babson College, and cofounder of the International Institute for Analytics. He also contributes to the MIT Initiative on the Digital Economy as a fellow, and as a senior advisor to Deloitte Analytics. Author of over a dozen management books, his latest is Only Humans Need Apply: Winners and Losers in the Age of Smart Machines.