Introduction
The semiconductor industry is on the brink of significant expansion, with Gartner forecasting a remarkable 33% increase in worldwide chip revenue for 2024.
This surge is largely driven by the burgeoning demand for AI accelerators and the integration of advanced AI capabilities into a variety of devices.
As industries continue to leverage AI for enhanced performance and efficiency, the market for AI chips is set to reach unprecedented heights.
Gartner’s latest research forecasts a significant rise in AI chip revenue, expecting it to reach $71.3 billion in 2024, marking a 33% increase from 2023.
This surge is attributed to two key factors:
Generative AI (GenAI): The rise of GenAI, which can create entirely new content like images or text, is driving the need for powerful AI chips in data centers. These chips handle the intensive processing required for GenAI applications.
AI PCs: Gartner anticipates that 22% of all PCs shipped in 2024 will be AI-enabled, and by 2026, 100% of enterprise PCs will have AI capabilities. This shift necessitates the integration of specialized AI chips, like Neural Processing Units (NPUs), into personal computers. These NPUs allow for longer battery life, quieter operation, and the ability to run AI tasks continuously in the background.
AI Chip Market Soars
Gartner’s latest research reveals that worldwide AI chip revenue will reach $71.3 billion in 2024, marking a 33% increase from 2023.
This growth stems from the rising demand for AI accelerators and the integration of AI capabilities into a wide array of devices, from data centers to personal electronics.
Where Are All These AI Chips Going?
The prediction indicates that AI chip revenue will increase from $53.7 billion in 2023 to $71.3 billion in 2024, and further to $92 billion in 2025.
In 2024, computer electronics will account for the largest share, with $33.4 billion, representing 47% of total AI chip revenue. 
Other significant contributors include automotive electronics at $7.1 billion and consumer electronics at $1.8 billion.
Most of the revenue will come from discrete and integrated application processors, discrete GPUs, and microprocessors used in computing.
These components are crucial for AI tasks, especially in high-performance computing environments.
Shift in AI Compute Needs
Gartner notes a shift in AI compute needs from model training to inference. Inference involves refining what the AI model has learned during training.
By 2028, AI inference tasks will account for more than 80% of workload accelerators in data centers, up from 40% in 2023.
AI Accelerators Drive Data Center Growth
AI accelerators in servers will become a $21 billion industry in 2024 and grow to $33 billion by 2028.
Generative AI is a significant driver of this demand, necessitating high-performance AI chips in data centers.
Gartner predicts that 25% of new servers will have workload accelerators by 2028, compared to just 10% in 2023.
These accelerators offload data processing from standard microprocessors, enhancing the efficiency and speed of AI workloads.
The Rise of AI PCs
Gartner is optimistic about the future of AI PCs.These are PCs with neural processing units that run AI models locally.
The firm predicts that by 2026, enterprises will purchase only AI PCs. This shift occurs as businesses seek to leverage AI for everyday tasks, enhancing productivity and user experience.
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Hyperscalers Lead the Charge
Major tech companies like AWS, Google, Meta, and Microsoft are developing in-house AI chips while still procuring hardware from established manufacturers like NVIDIA, AMD, Qualcomm, IBM, and Intel.
This dual approach allows them to optimize performance for specific workloads, control costs, and reduce reliance on third-party chips.
Custom AI Chips: A Growing Trend
Gartner analyst Gaurav Gupta highlights that hyperscalers are designing their own chips to better control their product roadmaps and leverage intellectual property synergies.
Custom-designed chips can improve operational efficiencies and reduce the costs of delivering AI-based services.
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Access to Cutting-Edge Manufacturing
Semiconductor foundries like TSMC and Samsung have made it easier for tech companies to access advanced manufacturing processes.
Firms like Arm and Synopsys provide intellectual property that facilitates custom chip design. The cloud and evolving semiconductor assembly and test service (SATS) providers also play a crucial role in this ecosystem.
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Conclusion
The Worldwide Chip Revenue is set for substantial growth, driven by the increasing integration of AI across various sectors.
Hyperscalers lead the charge in custom chip design, and the rising importance of AI PCs transforms the semiconductor industry.
Gartner’s predictions highlight the critical role AI chips will play in shaping the future of technology, from data centers to personal devices.
