AI infrastructure is the platform built where organizations can develop intelligent applications that are self-healing & protective and in addition also requires minimum human intervention. The IT infrastructure is filled by modern technologies like big data, mobility, and the internet of things. The requirement of intelligent infrastructure in today’s era is proving to harness the power of artificial intelligence-powered platforms. Artificial intelligence infrastructure sweeps every area of machine learning workflow. It permits software engineers, development teams, data scientists, and data engineers to effectively access and manage the computing resources to test, deploy and train AI algorithms.
The growing applications of cloud machine learning by the leading companies along with the surging popularity of hardware in data computing centers will drive the growth of the global AI infrastructure market. Furthermore, the wide utilization of artificial intelligence in several end-user industries like tourism, automotive, banking & financial, health care, and several other sectors is likely to scale up the global market significantly in the forthcoming years. In addition, the low prices of hardware devices along with the growing concentration on cloud computing in the data centers will accentuate the demand for AI infrastructure.
The leading manufacturers of GPU and CPU like Intel, Nvidia, and Samsung are significantly investing in the innovation of chips that are highly compatible with artificial intelligence solutions. Apart from these, the application-specific integrated circuits and field-programmable gate arrays are also being built for the same applications. The organizations utilizing AI and the ones that are looking forward to experiencing AI are likely to adopt giant infrastructure solutions that can bear the general AI workloads. This approach is similar to the platform architecture in the IT sector that offers a highly scalable infrastructure and is managed by one pool with the help of virtualization and software-defined orchestration to network, store, and process the data. All these aspects are projected to drive the market growth down the timeline.
The global AI infrastructure market can be segmented into end-user, deployment, function, technology, offering, and region.
By end-user, the market can be segmented into cloud service providers, government organizations, and enterprises.
By deployment, the market can be segmented into hybrid, cloud, and on-premises.
By function, the market can be segmented into inference and training.
By technology, the market can be segmented into deep learning and machine learning.
By offering, the market can be segmented into server software and hardware.
The hardware segment can further be bifurcated into networking, storage, memory, and processor.
North America accounts for the largest share in the global AI infrastructure market due to the ongoing technological advancements in the field of artificial intelligence in the region. Furthermore, a large number of companies are adopting AI infrastructure in the region. Also, the growing investments from key players to innovate advanced chips and circuits that are compatible with artificial intelligence solutions are likely to fuel the growth of the regional market in the forthcoming years.
Some of the significant players in the global AI infrastructure market are Arm Holdings, Cisco Systems, Inc., International Business Machines Corporation, Xilinx, Inc., Samsung, Microsoft Corporation, Amazon Web Service, Google LLC, Nvidia Corporation, and Intel Corporation. To cite, Wipro Limited in June 2020 announced that EON had offered multi-year infrastructure modernization and digital transformation services engagement.