AI Semiconductor Revenue to Reach $21B in 2024; Gartner

Gartner forecasts that 100% of enterprise PC purchases will incorporate AI by the end of 2026

Berenice Baker, Editor

May 30, 2024

2 Min Read
A conceptual image of a chip on a circuit board with red circuits
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The demand for AI processors to fuel growing enterprise applications will drive the expected global revenue from AI semiconductors up 33% to $71 billion in 2024, according to Gartner.

The tech research company’s new report, Forecast Analysis: AI Semiconductors, Worldwide, predicts this is set to grow further to $92 billion in 2025.

Tech shows in 2024 saw a growing number of PCs coming with an onboard AI capability and this is set to continue. Gartner predicts that 22% of PCs shipped in 2024 will be AI PCs and that by the end of 2026,  100% of enterprise PC purchases will be AI PCs.

According to Gartner, what sets AI PCs apart is that they include a neural processing unit (NPU) that enables them to run longer, quieter and cooler while AI tasks run continually in the background.

However, heavy-duty enterprise and research AI processing will continue to take place at data centers.

“Today, generative AI is fueling demand for high-performance AI chips in data centers,” said vice president analyst at Gartner Alan Priestley.

“In 2024, the value of AI accelerators used in servers, which offload data processing from microprocessors, will total $21 billion and increase to $33 billion by 2028.”

Revenue from AI chips for computer electronics is projected to record a record-high 47% share of the electronic segment, totaling $33.5 billion in 2024. In the same period, AI chips for automotive electronics are forecast to reach $7.1 billion and consumer electronics $1.8 billion.

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This move has also seen hyperscalers including AWS, Google, Meta and Microsoft invest in developing their own AI chips, whereas previously the focus had been on using high-performance graphics processing units (GPUs).

While research and development of new chips is an expensive undertaking, purpose-built chips can ultimately improve operational efficiencies, reduce the cost of delivering AI-based services to users and lower costs for users to access new AI-based applications.

“As the market shifts from development to deployment we expect to see this trend continue,” said Priestley.

About the Author(s)

Berenice Baker

Editor, Enter Quantum

Berenice is the editor of Enter Quantum, the companion website and exclusive content outlet for The Quantum Computing Summit. Enter Quantum informs quantum computing decision-makers and solutions creators with timely information, business applications and best practice to enable them to adopt the most effective quantum computing solution for their businesses. Berenice has a background in IT and 16 years’ experience as a technology journalist.

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