An AI strategy is no longer optional

If you haven’t committed to a comprehensive AI strategy, your competitors might already have an unfair advantage.

At the New York Times DealBook conference, Intel emphasized it was urgent that every company put an artificial intelligence (AI) strategy in place. The reason, in a word, is data. The data deluge continues to accelerate, with data points from the Internet of Things (IoT) alone expected to bring another 20 billion new sources of information within the next two years.

The amount of data coming into businesses exceeds the capability of humans to process it all. Companies need AI capabilities to enable new ways of making real-time business decisions, using machines that can process these vast quantities of data and learn from it. Having the right AI capabilities has already proven to make organizations more efficient and deliver a better customer experience—and a better bottom line.

AI can pay off in any number of ways. To cite a few real-world examples:

None of this is pie-in-the-sky; it’s happening now. Early AI adopters across virtually all industries are exposing valuable information that exists deep within data they already have. AI paves the way to solve complex medical and scientific challenges, and better predict the behavior of events and people.

One area that presents a clear example is cybersecurity. As hackers become more adept at their trade—and use AI technology to find vulnerabilities—AI provides an effective way for organizations to fight back. AI technology makes it possible to examine huge amounts of network traffic in real time, and correlate it to find patterns and events that constitute suspicious behavior. It can also be applied to historical patterns to detect advanced persistent threats, among the most pernicious types of attacks. In short, AI gives cybersecurity experts powerful tools to aid in their efforts to find and thwart security threats.

Companies are also learning that the infrastructure they already have in place will support AI modeling and applications. Recent significant performance gains for deep learning on Intel® Xeon®  Scalable processors enable organizations to use them to support jobs such as AI model training and inference, whether on premises or in low-cost cloud instances.