Global business value derived from artificial intelligence (AI) is projected to reach $1.2 trillion (Rs 80.3 trillion) in 2018, an increase of 70% from $692 billion (Rs 46.3 trillion) in 2017. The metric is seen reaching $3.9 trillion (Rs 261 trillion) in 2022, an increase of 467% from 2017 figure, but a rise of only 17% from $3.3 trillion in 2021, a report by research firm Gartner has shown.
Gartner said AI business value growth shows a typical S-shaped curve associated with an emerging technology. In 2018, the growth rate is estimated to be 70%, but it will slow down through 2022 and after 2020, the curve will flatten, resulting in low growth through the next few years.
The report also shows business value as derived by AI type. Initially, decision support/augmentation (such as deep neural networks) will represent 36% of the global AI-derived business value in 2018 and, by 2022, it will have surpassed all other types of AI initiatives to account for 44%.
Deep neural networks allow organisations to perform data mining and pattern recognition across huge data sets. This enables algorithms for decision support/augmentation to work directly with information that formerly required a human classifier.
"This new level of automation reduces costs and risks, and enables, for example, increased revenue through better micro-targeting, segmentation, marketing and selling," said John-David Lovelock, research vice-president at Gartner.
"In the early years of AI, customer experience is the primary source of derived business value. Customer experience is followed closely by cost reduction," Lovelock said.
However, in 2021, new revenue will become the dominant source, he said, as companies uncover 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," he 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 Gartner.
"One of the biggest aggregate sources for AI 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 applications," said Lovelock.