The AI infrastructure market is expected to grow from USD 23.7 billion in 2021 to USD 79.3 billion by 2026, at a CAGR of 27.3%.

Increased data traffic and the need for high computing power are driving the AI infrastructure market, as are increasing adoption of cloud machine learning platforms, increasingly large and complex datasets, a growing focus on parallel computing in AI data centres, and an increasing number of cross-industry partnerships and collaborations.

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Cloud service providers held the largest share of end users in the AI infrastructure market in 2020

The cloud mainly addresses three areas of operation: software-as-a-service (SaaS), infrastructure-as-a-service (IaaS), and platform-as-a-service (PaaS). Some of the major cloud service providers are AWS, Microsoft, IBM, Google, and Alibaba. These are the companies that provide cloud services to most of the companies worldwide. These companies are expected to lead the overall end user market for AI infrastructure.

Because of the great efficiency and economies of scale afforded by cloud computing, the number of data centre providers and cloud enterprises is expected to grow. Cloud service providers provide services to several customers using a shared infrastructure (i.e., operations, networking, data storage, and hardware) and help businesses save money on IT infrastructure.

Amazon Web Services (AWS), for example, offers IaaS for training and creating statistical models for inference.

Hybrid deployment held the largest share of AI infrastructure market in 2020

The market has been divided into three categories based on deployment type: on-premises, cloud, and hybrid.

A hybrid deployment approach combines on-premises infrastructure, private cloud services, and public cloud services to deliver mixed processing, storage, and services appropriate to the application. Cloud services assist firms in reducing costs and transforming into digital corporations. Businesses frequently employ a hybrid cloud to gain a competitive advantage because of its increased adaptability. Hybrid infrastructure, which combines many technologies and methodologies such as virtualization, private clouds, and other internal IT resources, has begun to be implemented in the automotive, healthcare, and industrial sectors.

Inference function to account for the largest share in the AI infrastructure market in 2021

On the basis of function, the market has been segmented into inference and training. The inference is computationally less intense than training. Unlike training, it does not include a backward pass to compute the error and update weights. It is usually a production phase wherein the model is deployed to predict the real-world data. An inference platform should enable easy integration of training into deployment systems, offer latency for demanding workloads, have scalability and a standard client interface for successful adoption.

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North America is leading the market for AI infrastructure in 2020

The worldwide AI infrastructure market is dominated by North America, and this trend is expected to continue in the foreseeable future. AI-based servers are predicted to be widely used in the United States and Canada. Because of their great focus on investing in R&D operations for the development of new technologies, these countries are technologically sophisticated economies in North America. The United States is one of the world's most advanced AI adopters.