AI Infrastructure Global Market Report 2024

AI Infrastructure Global Market Report 2024 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on ai infrastructure market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

Reasons to Purchase

• Gain a truly global perspective with the most comprehensive report available on this market covering 50+ geographies.
• Understand how the market has been affected by the coronavirus and how it is responding as the impact of the virus abates.
• Assess the Russia - Ukraine war's impact on agriculture, energy and mineral commodity supply and its direct and indirect impact on the market.
• Measure the impact of high global inflation on market growth.
• Create regional and country strategies on the basis of local data and analysis.
• Identify growth segments for investment.
• Outperform competitors using forecast data and the drivers and trends shaping the market.
• Understand customers based on the latest market shares.
• Benchmark performance against key competitors.
• Suitable for supporting your internal and external presentations with reliable high quality data and analysis
• Report will be updated with the latest data and delivered to you within 3-5 working days of order along with an Excel data sheet for easy data extraction and analysis.
• All data from the report will also be delivered in an excel dashboard format.

Where is the largest and fastest growing market for ai infrastructure? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? The ai infrastructure market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

• The market characteristics section of the report defines and explains the market.
• The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
• The forecasts are made after considering the major factors currently impacting the market. These include:

The impact of sanctions, supply chain disruptions, and altered demand for goods and services due to the Russian Ukraine war, impacting various macro-economic factors and parameters in the Eastern European region and its subsequent effect on global markets.

The impact of higher inflation in many countries and the resulting spike in interest rates.

The continued but declining impact of covid 19 on supply chains and consumption patterns.

• Market segmentations break down the market into sub markets.
• The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth. It covers the growth trajectory of COVID-19 for all regions, key developed countries and major emerging markets.
• The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
• The trends and strategies section analyses the shape of the market as it emerges from the crisis and suggests how companies can grow as the market recovers.

Scope

Markets Covered:

• 1) By Offerings: Hardware; Server Software
• 2) By Function: Training; Inference
• 3) By Technology: Machine Learning; Deep Learning
• 4) By Deployment Type: On-Premises; Cloud; Hybrid
• 5) By End User: Enterprises; Government Organizations; Cloud Service Providers
• Companies Mentioned: Nvidia Corporation; Intel Corporation; Oracle Corporation; Samsung Group; Micron Technology Inc.
• Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Russia; South Korea; UK; USA; Canada; Italy; Spain
• Regions: Asia-Pacific; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
• Time series: Five years historic and ten years forecast.
• Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
• Data segmentations: country and regional historic and forecast data, market share of competitors, market segments.
• Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
• Delivery format: PDF, Word and Excel Data Dashboard.

Executive Summary

AI infrastructure comprises IT infrastructure designed to collect data from various systems, preparing it for analysis and facilitating tasks such as outcome prediction, administrative task automation, and optimization of software-defined infrastructure technologies. This infrastructure is crucial for accessing and managing computing resources, enabling the testing, training, and deployment of AI algorithms in machine learning workflows.

The main components of AI infrastructure include hardware and server software. Hardware encompasses the physical components of computers and related devices. The functions of AI infrastructure involve training and inference, both integral to the machine learning and deep learning processes. Deployment types include on-premises, cloud-based, and hybrid solutions. Various end-users, such as enterprises, government organizations, and cloud service providers, leverage AI infrastructure to enhance their data processing and analysis capabilities.

The AI infrastructure market research report is one of a series of new reports from The Business Research Company that provides AI infrastructure market statistics, including AI infrastructure industry global market size, regional shares, competitors with an AI infrastructure market share, detailed AI infrastructure market segments, market trends and opportunities, and any further data you may need to thrive in the AI infrastructure industry. This AI infrastructure market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The ai infrastructure market size has grown exponentially in recent years. It will grow from $44.28 billion in 2023 to $58.07 billion in 2024 at a compound annual growth rate (CAGR) of 31.2%. The growth observed in the historical period can be attributed to several factors. These include the increased generation of data, advancements in deep learning technologies, a growing demand for real-time processing capabilities, compliance requirements with regulatory standards, and heightened concerns related to data privacy and security. These factors collectively contributed to the expansion and development of AI infrastructure during the specified historical period.

The ai infrastructure market size is expected to see exponential growth in the next few years. It will grow to $169.16 billion in 2028 at a compound annual growth rate (CAGR) of 30.6%. The anticipated growth in the forecast period can be attributed to various factors within the AI infrastructure landscape. These include advances in quantum computing, considerations for energy efficiency, the growth of explainable AI standards, an emphasis on personalization in customer experiences, and the rapid expansion of AI applications. Major trends expected in the forecast period encompass the swift adoption of AI across diverse industries, the expansion of edge AI, the development of AI-specific hardware, the prevalence of hybrid and multi-cloud deployments, the emergence of AI-optimized storage solutions, increased focus on AI security and ethical considerations, and collaborative efforts between AI and cloud providers. These trends are poised to shape and drive the growth of AI infrastructure in the coming forecast period.

The anticipated surge in AI infrastructure market growth stems from the escalating data traffic and the imperative for robust computing power. Data traffic signifies the volume of data coursing through a network, while high computing power denotes systems' capacity for rapid data processing and intricate calculations. High-Performance Computing (HPC) infrastructure stands as a linchpin for AI models, augmenting storage, networking, and data processing capabilities. Its pivotal role lies in enabling scalability for AI projects, facilitating swift workload processing during training stages, and significantly enhancing AI model accuracy and dependability within compressed timelines. A notable example is Ericsson's report in June 2022, revealing a 40% year-over-year surge in mobile network data traffic, underscoring this escalating trend. Similarly, in May 2022, the International Data Corporation highlighted that 50% of startups in the Asia-Pacific region prioritize high-performance computing infrastructure to grapple with life sciences' genomic data complexities, leveraging its potent computing prowess.

The trajectory of AI infrastructure market expansion aligns with the burgeoning demand for cloud services. These services encompass an array of on-demand computing resources and applications accessible over the internet. Within AI infrastructure, cloud services play a pivotal role in furnishing an adaptable, scalable platform for the development, deployment, and management of AI applications. They empower organizations to embark on innovative endeavors. Citing a September 2022 study by AAG IT Support Service, a global survey revealed a consistent uptick in heavy usage of cloud services among 753 technical and business professionals, rising from 53% in 2020 to 63% in 2022. This upward trend underscores the pivotal role of cloud services in propelling the growth trajectory of the construction industry.

A prominent trend steering the evolution of the AI infrastructure market revolves around technological advancements. Key industry players are directing their efforts towards innovating novel technological solutions to fortify their market positioning. Notably, Nvidia Corporation, a major entity in the AI infrastructure domain, unveiled in June 2021 the NVIDIA AI Launchpad-a comprehensive, cloud-native suite of AI and data analytics software. This solution aims to streamline the entire AI lifecycle, expediting the deployment of AI infrastructure and catering to diverse AI facets, from data center training and inference to extensive edge deployments. Furthermore, the compatibility of NVIDIA AI Launchpad with GPU and DPU-based systems furnishes enterprises with the ability to accelerate AI workloads, capitalizing on the security, isolation, and performance enhancements offered by DPUs.

Prominent entities within the AI infrastructure sphere are strategically forging partnerships to bolster their operational capacities. These collaborations involve the symbiotic utilization of each other's strengths and resources, aimed at securing mutual advantages and achieving collective success. A recent illustration of this trend occurred in October 2023 when VAST Data, a US-based technology company specializing in flash memory data storage, joined forces with Lambda, an expert in AI-optimized cloud solutions. The alliance seeks to fortify VAST Data's position in AI infrastructure by introducing an innovative hybrid cloud solution tailored specifically for AI and deep learning operations. This concerted effort positions VAST Data as the premier choice for specialized AI service providers, enhancing its leadership in AI infrastructure.

In July 2022, International Business Machines Corporation (IBM), a prominent player in information technology and AI infrastructure, made an undisclosed acquisition of Databand.ai. This strategic move is envisioned to augment IBM's product portfolio across data, AI, and automation domains, aiming to comprehensively address observability needs and facilitate organizations in ensuring secure and reliable data transactions. By integrating Databand.ai, an Israel-based AI infrastructure company, IBM aims to gain a competitive edge and reinforce its foothold in the market by offering enhanced and trustworthy AI-driven solutions.

Major companies operating in the ai infrastructure market report are Nvidia Corporation, Intel Corporation, Oracle Corporation, Samsung Group, Micron Technology Inc., Advanced Micro Devices Inc., International Business Machines Corporation, Google LLC, Microsoft Corporation, Amazon Web Services Inc., SK Hynix Inc., Cisco Systems Inc., Arm Limited, Xilinx Inc., Dell Inc., Synopsys Inc., Hewlett Packard Enterprise Company, Cadence Design Systems Inc., Toshiba Corporation, SenseTime Group Limited, Imagination Technologies Limited, Graphcore Limited, Habana Labs Limited, Meta Platforms Inc., Nutanix Inc., Pure Storage Inc., Wave Computing Inc., Tenstorrent Inc., Gyrfalcon Technology Inc., Cambricon Technologies Corporation Limited

North America was the largest region in the AI infrastructure market in 2023. Asia-Pacific is expected to be the fastest-growing region in the AI infrastructure market report forecast period. The regions covered in the ai infrastructure market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the ai infrastructure market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The AI infrastructure market includes revenues earned by entities by processor, storage memory, and software. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.