Artificial intelligence will be worth $1.2 trillion to the enterprise in 2018

Artificial intelligence will be worth $1.2 trillion to the enterprise in 2018

The artificial intelligence (AI) industry will be worth $1.2 trillion in 2018, with customer experience solutions creating the most business value.

On Wednesday, Gartner released estimates on the projected value of AI over the course of this year. According to the research firm, the global enterprise value derived from AI will total $1.2 trillion this year, a 70 percent increase from 2017.

AI-derived business value is projected to reach up to $3.9 trillion by 2022.

"AI promises to be the most disruptive class of technologies during the next 10 years due to advances in computational power, volume, velocity and variety of data, as well as advances in deep neural networks (DNNs)," said John-David Lovelock, research vice president at Gartner. "One of the biggest aggregate sources for AI-enhanced products and services acquired by organizations between 2017 and 2022 will be niche solutions that address one need very well."

These sort of needs may include methods to improve customer experiences, ways to drive new revenue streams, and means to reduce costs, whether operational or in serving existing products.

Companies including Google, Apple, Microsoft, IBM, and Nvidia are already heavily involved in the research and development of AI-based products and services. According to CB Insights, startups worldwide are springing up to specialize in artificial intelligence with an emphasis in industries including customer relationship management, automotive, sales, marketing, and commerce.

At first, Gartner believes strong growth will appear in the customer experience sector while enterprise players experiment with AI and offshoot technology, such as deep learning, neural networking, and machine learning software.

Virtual agents, for example, can take over simple customer requests and tasks from call centers, reducing the cost for companies in offering customer helplines. By taking over the simple issues, human operators are then free to dedicate their time to complicated issues, which, in turn, may improve customer service.

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