Worldwide AI Chips Revenue To Grow 33% In 2024, Total $71 Billion: Gartner

By the end of 2026, all enterprise PC purchases will be an AI PC, says the study.

<div class="paragraphs"><p>(Source: vecstock/freepik)</p></div>
(Source: vecstock/freepik)

Revenue from artificial intelligence semiconductors globally is expected to total $71 billion in 2024, an increase of 33% from 2023, according to a forecast from Gartner Inc. By 2025, worldwide AI chips revenue is expected to cross $91 billion.

Generative AI is fuelling the current demand for high-performance AI chips in data centres. In 2024, the value of AI accelerators used in servers, which offload data processing from microprocessors, is expected to total $21 billion. This is expected to increase to $33 billion by 2028, according to Gartner experts.

Gartner said that AI PC shipments will reach 22% of the total PC shipments in 2024, and by the end of 2026, 100% of enterprise PC purchases will be an AI PC. AI PCs include a neural processing unit, enabling AI PCs to run longer, quieter and cooler. These PCs have AI tasks running continually in the background, creating opportunities for leveraging AI in everyday activities.

While AI semiconductor revenue will continue to experience double-digit growth through the forecast period, 2024 will experience the highest growth rate during that period.

In 2024, AI chips revenue from computer electronics is projected to total $33.4 billion, which will account for 47% of total AI semiconductors revenue. AI chips revenue from automotive electronics is expected to reach $7.1 billion, and $1.8 billion from consumer electronics in 2024.

While greater focus is on the use of high-performance graphics processing units for new AI workloads, major hyperscalers such as Amazon Web Services, Google, Meta and Microsoft are investing in developing their own chips optimised for AI. While chip development is expensive, using custom designed chips can improve operational efficiencies, reduce the costs 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, this trend is expected to continue, according to Gartner.