Driven by customer experience, new revenue and cost reduction, global business value derived from Artificial Intelligence (AI) is projected to hit $1.2 trillion in 2018 — an increase of 70 per cent from 2017, a Gartner forecast said on Wednesday. Also Read - PlayGo BH-70 headphones launched in India with AI-driven active noise cancellation
AI-derived business value is forecast to reach $3.9 trillion in 2022. Also Read - Apple buys edge-based AI startup Xnor.ai for $200 million: Report
“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),” John-David Lovelock, Research Vice President at Gartner said in a statement. Also Read - Kolkata police plans to use camera with AI to detect crime
One of the biggest aggregate sources for AI-enhanced products and services acquired by enterprises between 2017 and 2022 will be niche solutions.
“Business executives will drive investment in these products, sourced from thousands of narrowly focused, specialist suppliers with specific AI-enhanced applications,” Lovelock added.
In the early years of AI, customer experience (CX) will be the primary source of derived business value as organisations see value in using AI techniques to improve every customer interaction.
“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,” said Lovelock.
“However, 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,” he Gartner executive noted.
By 2022, decision support/augmentation (such as deep neural networks) will have surpassed all other types of AI initiatives, to account for 44 per cent of global AI-derived business value.
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,” Lovelock explained.
Decision automation systems use AI to automate tasks or optimise business processes.
For now, decision automation accounts for just 2 per cent of the global AI-derived business value in 2018, but it will grow to 16 per cent by 2022.
Smart products account for 18 per cent of global AI-derived business value in 2018, but will shrink to 14 per cent by 2022 as other DNN-based system types mature and overtake smart products, Gartner said.