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세계의 AI 인프라 시장 : 성장, 동향, COVID-19의 영향, 예측(2021-2026년)

AI Infrastructure Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

리서치사 Mordor Intelligence Pvt Ltd
발행일 2022년 01월 상품코드 989431
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세계의 AI 인프라 시장 : 성장, 동향, COVID-19의 영향, 예측(2021-2026년) AI Infrastructure Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)
발행일 : 2022년 01월 페이지 정보 : 영문

본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문목차를 참고해주시기 바랍니다.

AI 인프라 시장 규모는 2021-2026년의 예측 기간 중 21%의 CAGR로 성장할 것으로 예상되고 있습니다. 전 세계의 많은 기업 및 IT 이그제큐티브는 이미 AI 테크놀러지에 고액의 투자를 시행하고 있습니다. AI는 주로 모든 것을 바꾸고 있습니다. AI가 보급하는 것에 따라 향후 조직은 업계 전체를 바꾸고 있는 매크로 레벨과 전략적 비지니스 의사결정에 영향을 미치는 미크로 레벨에서 AI 도입을 요구받게 됩니다. 이러한 큰 변화가 이러한 빠른 속도로 발생하고 있으므로 시장은 강력한 성장을 달성할 것으로 예상되고 있습니다.

  • AI의 경험이 풍부한 조직 또는 비지니스의 복수 영역에서 증대하는 요구에 대응하고자 하는 조직은 일반적인 AI 워크로드를 지원할 수 있는 폭넓은 인프라 솔루션을 채택할 것으로 기대되고 있습니다. 이 접근은 IT 전체에서 보급되고 있는 플랫폼 아키텍처와 유사하며, 서버 처리, 스토리지, 네트워크 전체에서 가상화와 소프트웨어 정의 오케스트레이션을 사용하여 단일 풀로서 관리되는 첨단 스케일러블 인프라 레이어를 제공합니다.
  • 네트워크 인프라는 AI를 지원하기 위해 필요한 규모로 고효율을 제공하는데 있어서 중요한 역할을 담당할 것으로 기대되고 있으며, 조직은 네트워크의 업그레이드가 필요하게 될 가능성이 있습니다. 딥러닝 알고리즘과 기계학습 알고리즘은 기업이 네트워크 효율을 달성하는데 도움이 됩니다. 예를 들면 기업은 데이터센터에 자동화된 인프라 관리툴을 도입할 필요가 있습니다.
  • 예를 들면 2020년 2월, Ericsson은 AI를 활용한 에너지 인프라 운영 솔루션을 발표했습니다. 이 솔루션은 AI와 첨단 데이터 분석을 활용하여 통신 서비스 프로바이더의 네트워크 인프라 전체의 에너지 소비를 최적화합니다.
  • 또한 다양한 최종사용자 업계에서 자동화의 성장도 시장의 성장을 지원하고 있습니다. 2019년 Capgemini 리포트에 따르면 유럽에서는 세계 TOP 제조업체의 51%가 운영에서 적어도 하나의 AI 사용 사례를 사용하고 있습니다.
  • 다양한 기업이 시장에서 AI 인프라 관련 솔루션을 제공하고 있으며, 기업이 AI 인프라를 활용할 수 있도록 하고 있습니다. 예를 들면 2020년 6월, Intel의 제3세대 Intel Xeon 스케일러블 프로세서와 하드웨어 및 소프트웨어 AI 포트폴리오에 대한 추가에 의해 고객은 AI 인프라를 지원하는 데이터센터, 네트워크, 지능형 엣지 환경에서 시행되는 AI 및 분석 워크로드의 개발과 사용을 가속할 수 있게 되었습니다.
  • 또한 다양한 국가가 시장의 성장을 촉진하고 있는 AI 에코시스템에 투자하고 있습니다. 예를 들면 2020년 1월, 인도 정부의 싱크탱크인 NITI Aayog는 'AIRAWAT'(AI Research, Analytics, and Knowledge Assimilation platform)로 불리는 자국내 최초의 AI 고유 클라우드 컴퓨팅 인프라를 셋업하기 위한 논문을 발표했습니다. 이 플랫폼은 AI 분야에서 새로운 테크놀러지의 연구개발을 안내하는 것을 목적으로 하고 있습니다.

세계의 AI 인프라 시장을 조사했으며, 시장의 개요, 시장 성장요인 및 저해요인 분석, 시장 기회, Covid-19의 영향, 제공·도입·최종사용자·지역별 시장 규모의 추이와 예측, 경쟁 구도, 주요 기업의 개요 등의 정보를 정리하여 전해드립니다.

목차

제1장 서론

제2장 조사 방법

제3장 주요 요약

제4장 시장 인사이트

  • 시장 개요
  • Porter's Five Forces 분석
  • COVID-19의 시장에 대한 영향 평가
  • 시장 촉진요인
    • 고성능 컴퓨팅 데이터센터에서 AI 하드웨어의 수요 증가
    • IIoT 및 자동화 테크놀러지의 애플리케이션 증가
    • 기계학습과 딥러닝 테크놀러지의 애플리케이션 증가
    • 자동차 및 헬스케어 등의 업계에서 생성되고 있는 방대한 양의 데이터
  • 시장 억제요인
    • 업계에서 숙련 전문가의 부족

제5장 시장 세분화

  • 제공별
    • 하드웨어
    • 소프트웨어
  • 도입별
    • 온프레미스
    • 클라우드
  • 최종사용자별
    • 기업
    • 정부
    • 클라우드 서비스 프로바이더
  • 지역별
    • 북미
    • 유럽
    • 아시아태평양
    • 라틴아메리카
    • 중동과 아프리카

제6장 경쟁 구도

  • 기업 개요
    • Intel Corporation
    • Nvidia Corporation
    • Samsung Electronics Co., Ltd.
    • Micron Technology, Inc.
    • Xilinx, Inc.
    • IBM Corporation
    • Google LLC
    • Microsoft Corporation
    • Amazon Web Services, Inc.
    • Cisco Systems, Inc.
    • Arm Holdings
    • Dell Inc.
    • Hewlett Packard Enterprise Company
    • Advanced Micro Devices
    • Synopsys Inc.

제7장 투자 분석

제8장 시장의 미래

KSA 21.03.03

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.

Key Highlights

  • 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.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

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

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