Edge artificial intelligence market surges on specialized chips and smart infrastructure

The global edge artificial intelligence market is expanding rapidly on the back of specialized chips, 5G rollout, and rising demand across automotive, healthcare, and smart city deployments, with software emerging as a key intelligence layer at the edge.

According to IMARC Group’s latest research publication, the global Edge Artificial Intelligence market size was valued at USD 18.30 Billion in 2024, and IMARC Group expects the market to reach USD 83.99 Billion by 2033, exhibiting a growth rate (CAGR) of 17.53% during 2025-2033. The report frames edge artificial intelligence as a response to demand for real-time, low-latency processing in use cases such as autonomous vehicles, industrial automation, and healthcare monitoring. By shifting computation from centralized clouds to local devices, edge artificial intelligence is positioned to improve responsiveness, reduce bandwidth needs, and strengthen privacy and security for sensitive data in sectors including finance, defense, and healthcare.

The article highlights rapid advances in specialized edge artificial intelligence hardware, with companies such as NVIDIA, Intel, Qualcomm, Arm, and Google building accelerators and chips tailored for on-device inference. Google’s seventh-generation artificial intelligence accelerator supports up to 9,216 chips, enabling large-scale workloads across agriculture, logistics, and smart cities, while Intel integrates Gaudi 3 chips into hybrid architectures in collaboration with IBM. The rollout of 5G is described as a key enabler, with U.S. investments of approximately USD 35 Billion in 5G infrastructure accelerating adoption in autonomous systems, augmented reality, and remote healthcare. Edge artificial intelligence is also closely tied to the expansion of the Internet of Things, as billions of connected devices increasingly require local processing for performance and cost control.

The industry overview underscores strong institutional and enterprise momentum, noting that the U.S. federal government increased artificial intelligence-related contracts by 1,200%, from USD 355 million to USD 4.6 Billion, and that automakers are investing nearly USD 50 billion in autonomous vehicle development, while the U.S. Army is committing up to USD 100 million for autonomous technologies. A survey of 301 U.S. chief information officers revealed that 97% have implemented or plan to implement edge artificial intelligence, and other surveys cited indicate that 83% of executives believe edge computing will be essential for competitiveness. Healthcare emerges as a major use case, with U.S. hospitals already having 10-15 edge devices connected per bed and estimates indicating that 75% of medical data will be generated at the edge, while the article also notes investment activity such as SANTECHTURE’s collaboration with CorroHealth for artificial intelligence-driven healthcare revenue cycle management in the GCC region.

On the infrastructure side, smart city and utility projects are deploying edge artificial intelligence for traffic optimization, public safety, water treatment, and grid management, with the International Telecommunication Union highlighting its importance for urban infrastructure, and the edge computing market is projected to experience nearly 40% annual growth. In the market segmentation, software is described as dominating by providing the intelligence layer for edge devices, and the telecom and IT segment is driven by enhanced network efficiency and real-time analytics, while North America leads regionally due to a strong technology base and early adoption of artificial intelligence and Internet of Things solutions. Recent product news includes Microsoft’s “Copilot Mode” in the Edge browser, Latent Artificial Intelligence’s Latent Agent platform for agentic edge deployments, Advantech’s AIR series edge artificial intelligence systems based on AMD hardware, Akamai’s Cloud Inference service offering 3x better throughput, 60% less latency, and 86% lower costs than traditional hyperscale infrastructure, and a Google and Synaptics collaboration to improve edge artificial intelligence for Internet of Things devices.

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