The global business value derived from artificial intelligence (AI) is expected to total $1.2 trillion this year.
That’s a fresh finding from Gartner’s research on the quantifiable value of AI, entitled: "Forecast: The Business Value of Artificial Intelligence, Worldwide, 2017-2025."
Rather than focusing on the dollars spent on AI, Gartner’s new forecast measures the impact of these technologies on revenue, costs and customer experience.
Research vice president at Gartner, John-David Lovelock, says 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).
He adds, "One of the biggest aggregate sources for AI-enhanced products and services acquired by enterprises between 2017 and 2022 will be niche solutions that address one need very well."
“Business executives will drive investment in these products, sourced from thousands of narrowly focused, specialist suppliers with specific AI-enhanced applications."
Gartner's forecast assesses the total business value of AI across all the enterprise vertical sectors covered by Gartner, and there are three different sources of AI business value: Customer experience: The positive or negative effects on indirect cost.
Customer experience is a necessary precondition for widespread adoption of AI technology to both unlock its full potential and enable value. New revenue: Increasing sales of existing products and services, and/or creating new product or service opportunity beyond the existing situation. Cost reduction: Reduced costs incurred in producing and delivering those new or existing products and services. In the report, Gartner predicts the 2018 AI growth rate to be 70%, but it will slow down through 2022.
Gartner reports the AI business value growth shows the typical S-shaped curve pattern associated with an emerging technology, by after 2020, the curve will flatten, resulting in low growth through the next few years.
"In the early years of AI, customer experience (CX) is the primary source of derived business value, as organisations see value in using AI techniques to improve every customer interaction, with the goal of increasing customer growth and retention,” continues Lovelock.
“CX is followed closely by cost reduction, as organisations look for ways to use AI to increase process efficiency to improve decision making and automate more tasks.”
However, according to Lovelock, in 2021, new revenue will become the dominant source, as companies uncover business value in using AI to increase sales of existing products and services, as well as to discover opportunities for new products and services.
“Thus, in the long run, the business value of AI will be about new revenue possibilities."
Moreover, breaking out the global business value derived by AI type, decision support (such as DNNs) will represent 36% of the global AI-derived business value in 2018.
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. According to Lovelock, DNNs allow organisations 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.
“This enables algorithms for decision support/augmentation to work directly with information that formerly required a human classifier,” he adds.
"Such capabilities have a huge impact on the ability of organisations 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."
Gartner’s report finds virtual agents, such as roboadvisors financial services, account for 46% of the global AI-derived business value in 2018 and 26% by 2022, as other AI types mature and contribute to business value.
Smart products have AI embedded in them, usually in the form of cloud systems that can integrate data about the user's preferences from multiple systems and interactions.
They learn about their users and their preferences to hyperpersonalise the experience and drive engagement.
Gartner’s research says smart products account for 18% of global AI-derived business value in 2018, but will shrink to 14% by 2022 as other DNN-based system types mature and overtake smart products in their contribution to business value.