▶ 調査レポート

AIインフラストラクチャの世界市場2021-2026:成長・動向・新型コロナの影響・市場予測

• 英文タイトル:AI Infrastructure Market - Growth, Trends, COVID-19 Impact, and Forecasts (2021 - 2026)

AI Infrastructure Market - Growth, Trends, COVID-19 Impact, and Forecasts (2021 - 2026)「AIインフラストラクチャの世界市場2021-2026:成長・動向・新型コロナの影響・市場予測」(市場規模、市場予測)調査レポートです。• レポートコード:MRC2103D073
• 出版社/出版日:Mordor Intelligence / 2021年1月
• レポート形態:英文、PDF、130ページ
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レポート概要
本調査レポートでは、世界のAIインフラストラクチャ市場について調査し、イントロダクション、調査手法、エグゼクティブサマリー、市場インサイト、提供方式別(ハードウェア、ソフトウェア)分析、展開方式別(オンプレミス、クラウド)分析、エンドユーザー別(企業、政府、クラウドサービスプロバイダー)分析、地域別分析、競争状況、投資分析、市場の将来など、以下の構成でお届けいたします。
・イントロダクション
・調査手法
・エグゼクティブサマリー
・市場インサイト
・世界のAIインフラストラクチャ市場規模:提供方式別(ハードウェア、ソフトウェア)
・世界のAIインフラストラクチャ市場規模:展開方式別(オンプレミス、クラウド)
・世界のAIインフラストラクチャ市場規模:エンドユーザー別(企業、政府、クラウドサービスプロバイダー)
・世界のAIインフラストラクチャ市場規模:地域別
・競争状況
・投資分析
・市場の将来

The AI Infrastructure Market is expected to register a CAGR of 21% during the forecast period (2021 – 2026). Many businesses and IT executives across the globe are already making significant investments in AI technologies. AI is primarily changing everything, and as it is becoming more prevalent, organizations in the near future will be forced to come to grips with it on a macro level as it is changing the entire industry, and on a micro-level, as it impacting the strategic business decisions. With such significant changes happening at such a fast pace, the market is expected to witness robust growth.

– The organizations that have more experience with AI, or the ones that are looking to respond to the increasing needs across multiple areas of their businesses, are expected to adopt broader infrastructure solutions that can support the general AI workloads. This approach is similar to the platform architecture prevalent across IT, which provides a highly scalable infrastructure layer that is managed as a single pool, with the usage of virtualization and software-defined orchestration across server processing, storage, and networking.
– The networking infrastructure is expected to play a crucial role in providing high efficiency at the scale required to support AI, and organizations may likely need to upgrade their networks. Deep learning algorithms, as well as machine learning algorithms, help companies to achieve network efficiencies. For example, companies should deploy automated infrastructure management tools in their data centers.
– For instance, In February 2020, Ericsson has launched an AI-powered Energy Infrastructure Operations solution, which leverages AI and advanced data analytics to optimize energy consumption across network infrastructure for communications service providers.
– Further, the growth in automation in different end-user industries has also been fueling the growth of the market studied. According to the Capgemini Report, 2019, in Europe, 51% of top global manufacturers use at least a single use case of AI in their operations.
– Different companies have been offering AI infrastructure-related solutions in the market studied, has been enabling the company to leverage their AI infrastructure. For instance, in June 2020, Intel its 3rd Gen Intel Xeon Scalable processors and additions to its hardware and software AI portfolio, enabling customers to accelerate the development and use of AI and analytics workloads running in the data center, network and intelligent-edge environments that support their AI infrastructure.
– Moreover, various countries have been investing in the AI ecosystem that has been propelling the growth of the market studied. For instance, in January 2020, the Indian government think tank NITI Aayog has released a paper to set up the country’s first AI-specific cloud computing infrastructure called ‘AIRAWAT’ (AI Research, Analytics, and Knowledge Assimilation platform). The platform aims to guide the research and development of new and emerging technologies in the field of AI.

Key Market Trends

Enterprise Segment is Expected to Witness Significant Growth

– Enterprises are increasingly recognizing the value associated with the incorporation of artificial intelligence (AI) into their business processes. They improve operational efficiency and reduce cost through automation of process flows.
– For instance, companies have been using autonomous processes to improve operations and change the face of customer service (for example, through AI-powered chatbots), while spurring innovation to new heights. According to an article published by Komando Technology, in 2020, chatbots are expected to cut business costs by USD 8 billion.
– Furthermore, as the focus of IT strategy moves from data management to intelligent action, enterprises have been increasingly recognizing the role of AI to support humans in problem-solving, decision making, and creative endeavors. Also, enterprises recognize that implementing and using AI is critical for their continued growth in the competitive environment with many potential opportunities, such as new opportunities using AI to drive innovation, make connections, identify, and foster new developments.
– Further, to leverage the AI opportunities, one of the first considerations for any enterprise is to have a suitable infrastructure to support AI developments. Moreover, AI solutions frequently demand new hardware and software integration to function. For instance, for collation and annotation of data source, scalable processing, or creating and fine-tuning models as new data become available requires AI solutions. Solutions include repurposing existing hardware and buying a one-off AI solution, building a broader platform to support multiple AI solutions, and outsourcing AI solution delivery. Thus, infrastructure plays a vital role in the growth of the AI landscape.

Europe is Expected to Witness Significant Growth

– Europe is expected to attain significant growth in the market primarily owing to countries such as Germany, that have been witnessing significant expansion in the AI field. For instance, In November 2018, the Federal Government of Germany launched its AI strategy developed jointly by the Federal Ministry of Education and Research, the Federal Ministry for Economic Affairs and Energy, and the Federal Ministry of Labour and Social Affairs. The strategy outlays the progress made in terms of AI in Germany, the goals to achieve in the future, and a plan of policy actions to realize them. The Federal Government of Germany planned to invest EUR 3 billion for the period 2019-2025 to implement the strategy.
– In terms of infrastructure, Germany’s government has intended to expand the current data infrastructure to create optimal conditions for the development of cutting-edge AI applications. All this investment is expected to fuel the growth of the market.
– Further, the strategy has outlaid many initiatives for improvement of the infrastructure in AI, such as building a trustworthy data and analysis infrastructure based on cloud platforms and upgraded storage and computing capacity, improving security and performance of information and communication systems with particular focus on the resilience of AI-systems in case of attacks, among others.
– Further, many companies in the country are expanding their foothold in the market through partnership and collaboration strategy. For instance, in June 2020, Wipro Limited announced that EON had given it a multi-year infrastructure modernization and digital transformation services engagement. The company will transform EON’s legacy data center operations to a hybrid cloud model by leveraging BoundaryLess Enterprise (BLE) framework and Wipro HOLMES, Artificial Intelligence (AI), and automation platform.

Competitive Landscape

The AI Infrastructure Market is highly competitive, owing to the presence of multiple large players in the market operating in domestic and international markets. The market appears to be moderately concentrated with the major players in the market are primarily adopting major strategies such as product innovations and mergers and acquisitions. The market is a technology-driven market that witnesses players are putting major efforts in R & D to widen the functionality of their solutions. Some of the major players in the market are Nvidia Corporation, Microsoft Corporation, Google, and IBM.

– July 2020: IBM Corporation announced the launch of Elastic Storage System (ESS) 5000 and updated Cloud Object Storage (COS) and Spectrum Discover as part of a new AI storage portfolio to support AI infrastructure. ESS 5000 is optimized for the Collect stage. This is based around IBM Power9 servers and operates the firm’s Spectrum Scale parallel file system.
– Dec 2019 – Intel Corporation announced that it had acquired Habana Labs, an Israel-based developer of programmable deep learning accelerators for the data centers, for approximately USD 2 billion. The acquisition will strengthen Intel’s artificial intelligence (AI) portfolio and accelerate its efforts in the fast-growing AI silicon market.
– Oct 2019 – Hewlett Packard Enterprise (HPE) announced the advancements to SimpliVity, the company’s flagship hyper-converged infrastructure (HCI) platform. This new generation of HCI is powered with artificial intelligence that simplifies virtual machine (VM) management and frees the IT staff to focus on innovation.

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レポート目次

1 INTRODUCTION
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS
4.1 Market Overview
4.2 Industry Attractiveness – Porter’s Five Forces Analysis
4.2.1 Bargaining Power of Consumers
4.2.2 Bargaining Power of Suppliers
4.2.3 Threat of New Entrants
4.2.4 Intensity of Competitive Rivalry
4.2.5 Threat of Substitute Products
4.3 Assessment of Impact of COVID-19 on the Market
4.4 Market Drivers
4.4.1 Increasing Demand for AI Hardware in High-Performance Computing Data Centers
4.4.2 Increasing Applications of IIoT and Automation Technologies
4.4.3 Rising Application of Machine Leaning and Deep learning Technologies
4.4.4 Huge Volume of Data Being Generated in Industries such as Automotive and Healthcare
4.5 Market Restraints
4.5.1 Lack of Skilled Professional in the Industry

5 MARKET SEGMENTATION
5.1 Offering
5.1.1 Hardware
5.1.1.1 Processor
5.1.1.2 Storage
5.1.1.3 Memory
5.1.2 Software
5.2 Deployment
5.2.1 On-premise
5.2.2 Cloud
5.3 End-user
5.3.1 Enterprises
5.3.2 Government
5.3.3 Cloud Service Providers
5.4 Geography
5.4.1 North America
5.4.1.1 United States
5.4.1.2 Canada
5.4.2 Europe
5.4.2.1 United Kingdom
5.4.2.2 Germany
5.4.2.3 France
5.4.2.4 Italy
5.4.2.5 Spain
5.4.2.6 Rest of Europe
5.4.3 Asia-Pacific
5.4.3.1 China
5.4.3.2 India
5.4.3.3 South Korea
5.4.3.4 Japan
5.4.3.5 Rest of Asia-Pacific
5.4.4 Latin America
5.4.5 Middle-East and Africa
5.4.5.1 Saudi Arabia
5.4.5.2 United Arab Emirates
5.4.5.3 Qatar
5.4.5.4 Israel
5.4.5.5 South Africa
5.4.5.6 Rest of Midlle-East and Africa

6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 Intel Corporation
6.1.2 Nvidia Corporation
6.1.3 Samsung Electronics Co., Ltd.
6.1.4 Micron Technology, Inc.
6.1.5 Xilinx, Inc.
6.1.6 IBM Corporation
6.1.7 Google LLC
6.1.8 Microsoft Corporation
6.1.9 Amazon Web Services, Inc.
6.1.10 Cisco Systems, Inc.
6.1.11 Arm Holdings
6.1.12 Dell Inc.
6.1.13 Hewlett Packard Enterprise Company
6.1.14 Advanced Micro Devices
6.1.15 Synopsys Inc.

7 INVESTMENT ANALYSIS

8 FUTURE OF THE MARKET