H. James Wilson

Let’s start with an overview of the state of AI in business today and its near-term implications.
AI is undoubtedly booming in business—at least in certain segments of it. In my work, I’ve helped design and analyze surveys suggesting that 25% to 30% of large U.S. companies are pursuing AI, many quite aggressively. Some have hundreds or even thousands of projects underway. The firms using AI most aggressively are large businesses with the most data—online platforms, financial services, telecommunications, and retail. Small- to medium-sized enterprises, business-to-business firms, and those in basic manufacturing industries are less likely to use AI. They typically lack not only the data to succeed with AI, but the expertise and awareness to pursue it effectively

Firms outside the United States are also pursuing AI at a slower pace, although there are aggressive adopters in China, the U.K., Canada, and Singapore.

As Emma Martinho-Truswell explains in her article, machine learning is perhaps the most important component of AI, but it has multiple variations—ordinary statistical machine learning, neural networks, deep learning neural networks, and so on. Versions of AI also use semantic approaches to understanding language and logic-based rule engines for making simple decisions. Each technology performs a particular set of tasks