Semiconductors designed to execute artificial intelligence (AI) workloads will be a 53.4 billion dollar market this year, up 20.9 percent from 2022, says Gartner. AI semiconductor revenue is predicted to increase 25.6 percent in 2024 and continue to experience double-digit growth through 2027. By then, AI chip revenue is expected to be more than double the size of the market in 2023, reaching 119.4 billion dollars.
“The developments in generative AI and the increasing use of a wide range AI-based applications in data centers, edge infrastructure and endpoint devices require the deployment of high performance graphics processing units (GPUs) and optimized semiconductor devices. This is driving the production and deployment of AI chips,” said Alan Priestley, VP Analyst at Gartner.
The need for efficient and optimized designs to support cost effective execution of AI-based workloads will result in an increase in deployments of custom-designed AI chips. “For many organizations, large scale deployments of custom AI chips will replace the current predominant chip architecture – discrete GPUs – for a wide range of AI-based workloads, especially those based on generative AI techniques,” said Priestley.
Generative AI is also driving demand for high-performance computing systems for development and deployment, with many vendors offering high performance GPU-based systems and networking equipment seeing significant near-term benefits. In the long term, as the hyperscalers look for efficient and cost-effective ways to deploy these applications, Gartner expects an increase in their use of custom-designed AI chips.
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In the consumer electronics market, Gartner analysts estimate that by the end of 2023, the value of AI-enabled application processors used in devices will amount to 1.2 billion dollars, up from 558 million dollars in 2022.