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Biz Value of AI Will Pass $1 Trillion This Year

The total business value derived from artificial intelligence (AI) is going to reach $1.2 trillion this year, industry watchers at Gartner believe. That's an increase of 70 percent over last year across all enterprise vertical sectors, globally, that the analyst firm covers. Gartner also expects that number to reach $3.9 trillion by 2022.

In the report, "Forecast: The Business Value of Artificial Intelligence, Worldwide, 2017-2025," Gartner identifies three sources of AI business value: customer experience (CX), which is "a necessary precondition for widespread adoption of AI technology to both unlock its full potential and enable value;" new revenue from increased sales of existing products and services, and/or new products and services; and reduced costs incurred in the production and delivery of those new or existing products and services.

"The value is being derived first from the use of AI in ways that improve customer interactions, which leads to customer growth and retention," explained John-David Lovelock, research vice president at Gartner. "Chances are, you use AI every day. There's Apple's Siri and Amazon's Alexa, of course, but we are seeing AI in call centers, and stores are making money with chatbots on their websites."

"Next is value derived from cost reduction," he added, "where AI is used to improve process efficiency, decision making, and to automate tasks. But by 2021, it's going to be about new revenue. AI will be used to increase sales of existing products and services, and in new products and services."

One of the biggest aggregate sources for AI-enhanced products and services in the enterprise between 2017 and 2022 will be niche solutions that address one need very well, Lovelock said. He expects business executives to drive investment in these products, which will be sourced from thousands of narrowly focused, specialist suppliers with specific AI-enhanced applications.

So-called smart products, which have AI embedded in them, currently account for 18 percent of global AI-derived business value, the report states, but that will shrink to 14 percent by 2022 as other DNN-based system types mature "and overtake smart products in their contribution to business value."

By 2022, decision support/augmentation will have surpassed all other types of AI initiatives to account for 44 percent of global AI-derived business value, Gartner believes. Radiology departments, for example, have been using AI successfully for years in this way to improve diagnostic outcomes.

AI promises to be the most disruptive class of technologies during the next 10 years, because of advances in computational power, volume, velocity, and variety of data, Lovelock said, but also because of advances in compute techniques, such as deep neural networks (DNNs), which are essentially neural nets with many layers.

"DNNs allow organizations to perform data mining and pattern recognition across huge datasets not otherwise readily quantified or classified, creating tools that classify complex inputs that then feed traditional programming systems," Lovelock said in a statement. "This enables algorithms for decision support/augmentation to work directly with information that formerly required a human classifier. "Such capabilities have a huge impact on the ability of organizations to automate decision and interaction processes. This new level of automation reduces costs and risks, and enables, for example, increased revenue through better microtargeting, segmentation, marketing and selling."

Lovelock has been involved with AI since the 1980s, so he has something of a historical perspective on the technology.

"This is our third kick at the can," Lovelock said. "We started back in the 1950s, then an AI winter set it. We tried again in the 1980s, but then we saw another cold snap. The difference now is that AI is fit for use. It'll be years before we get anywhere near delivering on the current hype, but I don't see any chilly weather ahead this time around."

Although this market sector is expanding, fast, these are still early days for AI, in part at least, because the tools are not yet accessible to mid-level coders, Lovelock said. "When we get those tools in place, things will really start moving," he said.

Gartner clients can read the entire report online. This report is part of a collection of special reports, which includes "The Future of Work and Talent: Culture, Diversity, Technology" and "Deliver Artificial Intelligence Business Value."

About the Author

John has been covering the high-tech beat from Silicon Valley and the San Francisco Bay Area for nearly two decades. He serves as Editor-at-Large for Application Development Trends (www.ADTMag.com) and contributes regularly to Redmond Magazine, The Technology Horizons in Education Journal, and Campus Technology. He is the author of more than a dozen books, including The Everything Guide to Social Media; The Everything Computer Book; Blobitecture: Waveform Architecture and Digital Design; John Chambers and the Cisco Way; and Diablo: The Official Strategy Guide.

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