AI Hardware Market Size, Share & Trends Analysis Report By Hardware Component (Processors, Memory, Storage, Network, Specialized Embedded Hardware), By Application, By End Use, By Region, And Segment Forecasts, 2025 - 2033

AI Hardware Market Summary

The global AI hardware market size was estimated at USD 86.79 billion in 2024 and is projected to reach USD 691.04 billion by 2033, growing at a CAGR of 25.1% from 2025 to 2033. The market is expanding rapidly, driven by the rising adoption of Artificial Intelligence (AI) across industries such as consumer electronics, automotive, healthcare, and defense.

Growth is fueled by increasing demand for high-performance processors, memory, and specialized chips to support training and inference of complex AI models. Chip designs are now being optimized to handle AI workloads directly on devices. This advancement enables smartphones, wearables, and PCs to process complex models with greater efficiency. The reduced reliance on cloud connectivity ensures faster performance for real-time applications. At the same time, keeping computations local enhances data privacy and security. Together, these developments are driving a stronger shift toward on-device AI processing.

For instance, in September 2025, Arm Holdings plc, a UK-based semiconductor company, launched its Lumex chip designs, engineered for artificial intelligence on mobile devices, spanning from low-power wearables to advanced smartphones capable of running large AI models locally without relying on cloud access. The Lumex series, part of Arm’s Compute Subsystems business, is built on 3-nanometer manufacturing nodes.

The development of specialized chips for complex AI tasks is driving the growth of the AI hardware industry. These chips enhance efficiency and speed for real-world AI applications, prompting organizations to invest in advanced hardware capable of handling large-scale computations. This emphasis on practical AI workloads is fostering innovation in chip design, memory architecture, and system integration. It also encourages manufacturers to provide scalable solutions that support diverse AI applications. Companies are increasingly developing high-performance, task-focused chips that enable practical AI solutions efficiently. For instance, in September 2025, NVIDIA Corporation, a U.S.-based technology company specializing in GPUs and AI hardware, announced its Rubin CPX GPU, designed for disaggregated AI inference, where compute-focused chips handle context processing and memory-bandwidth-optimized chips manage generation tasks. The Rubin CPX, paired with standard Rubin GPUs in the upcoming Vera Rubin NVL144 CPX rack, will deliver up to 8 exaFLOPs of performance, targeting large AI workloads such as multi-step reasoning and AI video generation.

Global AI Hardware Market Report Segmentation

This report forecasts revenue growth at the global, regional, and country levels and provides an analysis of the latest industry trends and opportunities in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global AI Hardware market report based on hardware component, application, end use, and region:

• Hardware Component Outlook (Revenue, USD Billion, 2021 - 2033)
• Processors
• Memory
• Storage
• Network
• Specialized Embedded Hardware
• Application Outlook (Revenue, USD Billion, 2021 - 2033)
• Machine Learning/Deep Learning
• Computer Vision
• Natural Language Processing
• Robotics
• Generative AI
• End Use Outlook (Revenue, USD Billion, 2021 - 2033)
• Consumer Electronics
• Automotive
• Healthcare
• Aerospace and Defense
• Others
• Regional Outlook (Revenue, USD Billion, 2021 - 2033)
• North America
• U.S.
• Canada
• Mexico
• Europe
• UK
• Germany
• France
• Asia Pacific
• China
• Japan
• India
• Australia
• South Korea
• Latin America
• Brazil
• Middle East & Africa (MEA)
• KSA
• UAE
• South Africa

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