Global business value derived from artificial intelligence will reach $1.2 trillion in 2018, an increase of 70% from last year, according to Gartner. By 2022, that figure will be $3.9 trillion.
Gartner’s forecast assesses the total business value of AI across 17 enterprise vertical sectors it covers — among them insurance, banking and securities — based on customer experience, new revenue, and cost reduction. Gartner does not break out financial services as a separate value, a spokeswoman said.
“AI promises to be the most disruptive class of technologies during the next 10 years due to advances in computational power, volume, velocity and variety of data, as well as advances in deep neural networks,” said John-David Lovelock, research vice president at Gartner, in a statement.
“AI-enhanced products and services acquired by enterprises between 2017 and 2022 will be niche solutions that address one need very well. Business executives will drive investment in these products, sourced from thousands of narrowly focused, specialist suppliers with specific AI-enhanced applications.”
Forecast of Global AI-Derived Business Value (US$ Billions)
Source: Gartner (April 2018)
In the early years, customer experience will take the lead, with AI techniques being used to improve every customer interaction in the hopes of increasing customer growth and retention.
That will be followed closely by cost reduction, as organizations look for ways to use AI to increase process efficiency to improve decision making and automate more tasks.
However, in 2021, new revenue will dominate, 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,” Lovelock said.
DNNs will dominate
Breaking out the figures by AI type: decision support/augmentation, such as deep neural networks, will represent 36% of the global AI-derived business value in 2018, rising to 44% by 2022 to surpass all other types of AI initiatives.
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.
This enables algorithms for decision support and 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,” said Lovelock.
Chatbots and robo-advisors early runners
Virtual agents, such as chatbots, allow corporate organizations to reduce labor costs as they take over simple requests and tasks from a call center, help desk and other service human agents, while handing over the more complex questions to their human counterparts.
They can also provide uplift to revenue, as in the case of robo-advisors in financial services.
Agents 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, according to Gartner’s report.
A major area for growth is decision automation, which accounts for just 2% of the global AI-derived business value in 2018, but it will grow to 16% by 2022.
Decision automation systems use AI to automate tasks or optimize business processes. They are particularly helpful in tasks such as translating voice to text and vice versa, processing handwritten forms or images, and classifying other rich data content not readily accessible to conventional systems.
As unstructured data and ambiguity are the staple of the corporate world, decision automation — as it matures — will bring tremendous business value to organizations.
“Smart products” however are seen dropping in proportionate value, currently accounting for 18% of global AI-derived business value in 2018, but shrinking to 14% by 2022 as other DNN-based system types mature and overtake smart products.
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 hyper-personalize the experience and drive engagement.