Artificial intelligence is seeping into enterprises in various ways. Smart enterprises integrate AI into their business strategy.

I have spent more than 25 years researching and implementing AI technologies -- from the days of IBM's "discovery server" which lead to "OmniFind" and then became part of their flagship AI brand Watson to various iterations of text analytics and machine learning applications to prototypes and deployed projects using conversational technologies. During these cycles of new technology – all of which were marked by hype, missed expectations and eventual adoption -- I have seen patterns of success and failure as the AI landscape has evolved. In The AI-Powered Enterprise, I seek to help businesses deliver AI's promise of revolutionary change. Achieving this goal means avoiding the most common mistakes I've seen companies make, including: Executives tend to think AI technology is beyond their ability to understand. The complex programming may be out of reach for many, but the basic functioning needs to be explainable and understandable in business terms.

These and many other insights are from Capgemini Research Institute's research of enterprises' AI pilot, production and spending during the pandemic provide insights into what differentiates AI-at-scale leaders versus organizations struggling to get results. The AI-powered enterprise: Unlocking the potential of AI at scale is based on 950 interviews with AI leaders in enterprises with annual revenues between $1B to $25B, distributed across 11 nations. The study was completed in March and April 2020. For additional details on the methodology, please see pages 31 and 32. Capgemini has made the report available for free download here (PDF, 40 pp, no opt-in).