Skip to main content

How AI Business Value Will Reach $3.9 Trillion in 2022

More CIOs and CTOs are exploring the commercial value of intelligent systems that can enhance their organization's performance. Global business value from artificial intelligence (AI) is forecast to total $1.2 trillion in 2018 -- that's an increase of 70 percent from 2017, according to the latest market study by Gartner.

Moreover, AI-derived business value is forecast to reach $3.9 trillion in 2022. According to the Gartner assessment, there are three different sources of AI business value:

  1. 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.
  2. New revenue: Increasing sales of existing products and services, and/or creating new product or service opportunity beyond the existing situation.
  3. Cost reduction: Reduced costs incurred in producing and delivering those new or existing products and services.

AI Technology Market Development

"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.

Gartner analysts believe niche solutions that address one specific use-case very well will be a key adoption strategy for new AI-enhanced products and services acquired by the leading enterprises.

AI business value growth shows the typical S-shaped curve pattern associated with an emerging technology. In 2018, the growth rate is estimated to be 70 percent, but it will slow down through 2022. After 2020, the curve will flatten, resulting in somewhat low growth over time.

In 2021, driving new digital revenue streams will become the dominant application, 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.

Breaking out the global business value derived by AI type, decision support or augmentation (such as DNNs) will represent 36 percent of the global AI-derived business value in 2018. By 2022, these apps will have surpassed all other types of AI initiatives to account for 44 percent of global AI-derived business value.

"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 or augmentation to work directly with information that formerly required a human classifier," said Mr. Lovelock.

'Virtual agents' allow corporate organizations to reduce human 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.

Virtual agents will account for 46 percent of the global AI-derived business value in 2018, and 26 percent by 2022, as other AI types mature and contribute to business value.

Outlook for Emerging AI Applications Growth

As unstructured data growth accelerates in the corporate world, utilizing decision automation will bring significant new business value to organizations. For now, decision automation accounts for just 2 percent of the global AI-derived business value in 2018, but it will grow to 16 percent by 2022.

Furthermore, smart products account for 18 percent of global AI-derived business value in 2018, but will likely shrink to 14 percent by 2022 as other DNN-based system types mature and overtake smart products in their contribution to business value.

Popular posts from this blog

IoT Device Management Demand Gains Momentum

More forward-thinking CIOs and CTOs are focused on the adoption of the Internet of Things (IoT). Management challenges are top of mind for those who have already deployed a large number of sensors and associated network edge devices. Device management services are evolving in response to a greater breadth of new device technologies such as edge intelligence and related connectivity solutions, as well as the customer scalability and security of IoT deployments. But forward-looking suppliers are also preparing for a world where 41.3 percent of the connected devices will be using some form of Low Power Wide Area (LPWA) technologies by 2026. IoT Device Management Market Development Since IoT customers increasingly need to manage a larger fleet of connected devices, ABI Research now forecasts that IoT device management services will exceed $36.8 billion in revenues by 2026. Standardization is beginning to play a bigger role in device management services, as more connected devices use LPWA t

Anywhere, Anytime Workplace Demand for SASE

The ongoing adoption of flexible working models within the enterprise market has significant implications for typical IT organizations that must now support knowledge workers and front-line employees that operate outside the corporate network perimeter. The global COVID-19 pandemic created IT networking and security challenges. The expansion of the distributed workforce, an increasing reliance on cloud computing infrastructure, and the requirement to securely connect online employees -- wherever they choose to work, at any given moment in time. Legacy IT solutions that have rigid network underlays and a requirement for on-premises infrastructure cannot adequately deal with these trends. This 'Anywhere, Anytime Workplace' led to demand for new Secure Access Service Edge (SASE) solutions, with networking and security delivered as-a-service. Anywhere, Anytime Workplace Market Development   Although converging networking and security capabilities offer enterprises a promising solut

Cloud Edge Computing Demand Continues to Grow

Public cloud computing solutions are moving closer to the edge of networks where CIOs and CTOs are hosting new apps. The edge journey is well underway for forward-looking organizations as they seek to connect with customers, improve operational efficiency, and adopt digital business technologies to drive innovation. The latest worldwide market study by International Data Corporation (IDC) found that three-quarters of organizations plan to increase their edge computing spending over the next two years with an average increase of 37 percent. A combination of factors is driving this increased spending at the edge. Cloud Edge Computing Market Development The performance requirements of expanding workloads and new use cases that leverage artificial intelligence (AI) and machine learning (ML) demand greater compute capacity at the edge. In addition, the amount of data being stored in edge locations are rapidly expanding, and organizations plan to keep this data longer. As a result, the numbe