The firm expects the edge AI chipset market to reach $12.2 billion in revenues, outpacing the cloud AI chipset market, which will reach $11.9 billion in 2025. The transition, says the firm, will be propelled by the increasing focus on low latency, data privacy, and the availability of low-cost and ultra-power-efficient AI chipsets.

Currently, the cloud is the center of AI, with most AI training and inference workloads happening in the public and private clouds. Traditionally, the centralization of these workloads in the cloud brings the benefits of flexibility and scalability.

However, says the firm, the industry has witnessed a shift in the AI paradigm driven by the need for privacy, cybersecurity, and low latency. There is an emergence of performing AI training and inference workloads on gateways, devices, and sensors. Recent advancements in key domains, including connectivity to cloud computing, new AI learning architecture, and high-performance computational chipsets, have played a critical role in this shift, says the firm.

“As enterprises start to look for AI solutions in the areas of image and object recognition, autonomous material handling, predictive maintenance, and human-machine interface for end devices, they need to resolve concerns around data privacy, power efficiency, low latency, and strong on-device computing performance,” says Lian Jye Su, Principal Analyst at ABI Research. “Edge AI will be the answer to this. By integrating an AI chipset designed to perform high-speed inference and quantized federated learning or collaborative learning models, edge AI brings task automation and augmentation to device and sensor levels across various sectors. So much that it will grow and surpass the cloud AI chipset market in 2025.”

As a result, says the firm, this is a prime opportunity for chipset vendors with a diverse range of product offerings to capitalize and shine, instead of relying solely on a particular niche. As a prime example, in 2019, chipset conglomerate Intel witnessed strong growth in Mobileye, its ADAS chipset subsidiary, and overtook Nvidia as the leading-edge AI vendor. Intel is expected to continue to see high demands for its cloud AI chipset and experience strong demand for its Mobileye, Movidius, and FPGA product solutions.

In the consumer market, COVID-19 has disrupted the demand for many smart devices – notably smartphones, smart home, and wearables – which has impacted the deployment of AI accelerators targeting these devices. At the same time, implementation in industrial manufacturing, retail, and other verticals have been postponed or put on hold.

“Nonetheless,” says Su, “ABI Research expects the market to rebound in 2022. It is important to note that the impact on the chipset supply chain has been relatively minimal since fabrication factories in Singapore and Taiwan remained operational during the outbreak.”

Vendors of key connectivity technologies such as 5G, Wi-Fi 6, and autonomous solutions such as autonomous vehicles see minimal impact to their product roadmaps. They are continuing with their trials and deployments, foretelling a quick rebound in demand for edge AI chipset beyond 2022.

“Catalyzing many other emerging technologies,” says Su, “edge AI will pave the way for a variety of new business opportunities in the consumer and enterprise segments.”

For more, see the firm’s Artificial Intelligence and Machine Learning market data report.

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