The AI chips market is currently one of the hottest sectors in the technology industry. Gartner is forecasting that semiconductors designed to execute AI workloads would represent a US$53.4 billion revenue opportunity for the entire semiconductor industry this year – a massive 20.9% increase from 2022.
“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,” Alan Priestley, VP Analyst at Gartner said.
“This is driving the production and deployment of AI chips,” Priestley added. The AI chips sector holds such potential that Gartner even predicts revenue to continue to experience double-digit growth through the forecast period, increasing 25.6% in 2024 to US$67.1 billion. “By 2027, AI chips revenue is expected to be more than double the size of the market in 2023, reaching US$119.4 billion,” Gartner noted.
As the usage of AI-based workloads in the workplace grows, many more sectors and IT organisations will adopt systems with AI chips. The increasing popularity of generative AI models like ChatGPT is driving demand for efficient and optimized AI chips. These chips are needed to power the computationally intensive workloads required by these models. Gartner’s recent survey of 2,500 executive leaders found that 45% of them have increased their AI investments in response to the publicity surrounding ChatGPT.
“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,” says Priestley.
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