In recent years, has left the machine room and entered the world of mainstream business. Within the next five years, will have a major impact in all industries, according to research conducted by BCG and MIT Sloan Management Review. The research found that more than 70% of executives expect to play a significant role at their companies.
Today’s algorithms already support remarkably accurate machine sight, hearing, and , and they can access global repositories of information. performance continues to improve, thanks to and other advanced techniques, a staggering level of growth in data, and continuing advances in raw processing power. These developments have led to an explosion in -enabled business applications , analogous to the Cambrian era, when the development of eyesight contributed to a remarkable worldwide increase in species diversity.
Strive for more winners than losers
As always, this new era will have winners and losers. But our research with MIT suggests that if current patterns continue, the separation between the two could be especially dramatic and unforgiving. The data revealed markedly different levels of understanding and adoption even within the same industry. In insurance, for instance, China’s Ping An Group started development five years ago and is now incorporating the technology in various services, while other insurers are just starting to experiment with the simplest applications. Overall, executives from many companies reported that their organizations lacked a basic understanding of .
As a starting point, this report aims to provide an intuitive and practical comprehension of . At a deeper level, it also discusses many current and potential use cases for and examines the impact of on industry value pools, the future of work, and the pursuit of competitive advantage. Finally, it offers some practical guidance on how to introduce and spread within large organizations.
Although elements of are available in the market, the hard work of managing the interplay of data, processes, and technologies happens in-house.
Is Not an Off-the-Shelf Solution
is not plug and play. Companies cannot simply “buy intelligence” and apply it to their problems. Although; elements of are available in the market, the hard work of managing the interplay of data, processes, and technologies happens in-house.
The conceptual framework for putting to work is fairly intuitive. (See Exhibit 1.) In a nutshell, algorithms absorb data, process it, and then generate actions. The process depends on proper integration of several layers of technology, however, and identifying a specific path from data to action often bedevils companies. […]