Chips specially designed for artificial intelligence (AI) work are poised to generate 21 per cent more in revenue this year to reach $53.4 billion, as enterprises continue to adopt AI capabilities, a new study from Gartner has shown.
The growth from last year will be largely underpinned by developments in the highly-popular generative AI segment, the US-based research firm said in its latest industry update.
Growth in revenue is set to accelerate rising by more than a quarter to $67.2 billion next year and more than double to nearly $120 billion by 2027, it said.
In the consumer electronics market alone, the value of AI-enabled application processors used in devices will more than double annually to $1.2 billion by the end of this year, Gartner analysts estimate.
This will be driven by the expected rush of more industries and IT organisations integrating systems that utilise AI into their operations, as the use of AI-based workloads is expected to mature further, it said.
"The need for efficient and optimised designs to support cost-effective execution of AI-based workloads will result in an increase in deployments of custom-designed AI chips," Gartner said.
AI has long been used by businesses in their operations but has gained momentum with the advent of generative AI, made popular by Microsoft-backed Open AI's ChatGPT, which became a sensation as it is capable of producing various kinds of data, including audio, code, images, text, simulations, 3D objects and videos.
Investors put more than $4.2 billion into generative AI start-ups in 2021 and 2022 through 215 deals after interest surged in 2019, recent data from CB Insights found.
Already, manufacturers are tapping into the technology's potential.
Nvidia, one of the world's leading chipmakers, saw its share price soar about 174 per cent in the past 12 months as it tapped into the generative AI bonanza with powerful new semiconductor offerings – helping it join the highly-elite, trillion-dollar market capitalisation club.
SoftBank Group's British semiconductor unit Arm, meanwhile, is stirring a buzz with its potential blockbuster initial public offering in September, which could be the technology sector's third biggest listing of all time and the largest IPO in the US this year.
The company aims to focus less on the smartphone market and target customers that make chips for data centres, which are increasingly integrating AI capabilities. Arm says its energy-efficient technology is a good fit for data centres that consume considerable amounts of power.
Gartner this week also described generative AI as overhyped and positioned it at the peak of “inflated expectations” for emerging technology in 2023, close behind AI-augmented software engineering and cloud-native technology, in its latest Hype Cycle For Emerging Technologies report.
The sensational technology is leading a trend centred around creating new opportunities for innovation, potentially delivering transformational benefits within the next two to 10 years, Gartner said.
Generative AI, in particular, is expected to deliver these benefits within two to five years before plateauing, a state in which little or no progress is being made after a period of development, it said.
“The developments in generative AI and the increasing use of a wide range AI-based applications in data centres, edge infrastructure and endpoint devices require the deployment of high performance graphics processing units and optimised semiconductor devices," Alan Priestley, a vice-president analyst at Gartner, wrote in this week's report.
"This is driving the production and deployment of AI chips.”
Generative AI is also driving demand for high-performance computing systems that are being positioned for development and use, Gartner said.
As a result, many semiconductor vendors are offering high-performance GPU-based systems and networking equipment, as they see significant near-term benefits on the horizon.
"In the long term, as the hyper-scalers look for efficient and cost-effective ways to deploy these applications, Gartner expects an increase in their use of custom-designed AI chips," the study said.