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세계의 AIOps : 시장 : 예측(2021-2026년)

Global AIOps Market - Forecasts from 2021 to 2026

리서치사 Knowledge Sourcing Intelligence
발행일 2021년 12월 상품코드 1060128
페이지 정보 영문 124 Pages 배송안내 1-2일 (영업일 기준)
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세계의 AIOps : 시장 : 예측(2021-2026년) Global AIOps Market - Forecasts from 2021 to 2026
발행일 : 2021년 12월 페이지 정보 : 영문 124 Pages

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

세계의 AIOps 시장 규모는 2019년에 16억 9,200만 달러를 기록하고, 예측기간 중 18.27%의 CAGR로 확대되어 2026년에 54억 7,700만 달러가 될 것으로 예측됩니다. 시장을 견인하는 요인으로 IT 운영을 위한 AI 기반 서비스에 대한 수요 증가, 데이터 확장성이나 예측 분석의 필요성 등을 들 수 있습니다.

세계의 AIOps 시장을 조사했으며, 시장 규모와 예측, COVID-19의 영향, 시장 성장 촉진요인 및 과제, 시장 동향, 컴포넌트별, 제공별, 전개 모델별, 기업 규모별, 최종 이용 업계별, 지역별 시장 분석, 경쟁 상황, 주요 기업 개요 등의 체계적인 정보를 제공합니다.

목차

제1장 서론

  • 시장 개요
  • Covid-19 시나리오
  • 시장 정의
  • 시장 세분화

제2장 조사 방법

  • 조사 데이터
  • 가정

제3장 주요 요약

  • 조사 하이라이트

제4장 시장 역학

  • 시장 성장 촉진요인
  • 시장 성장 억제요인
  • Porter's Five Forces 분석
    • 공급 기업의 협상력
    • 신규 참여업체의 위협
    • 구매자의 협상력
    • 대체품의 위협
    • 경쟁 기업간 경쟁 관계
  • 업계의 밸류체인 분석

제5장 세계의 AIOps 시장 : 컴포넌트별

  • 서론
  • 데이터 수집과 분석
  • 머신러닝과 AI

제6장 세계의 AIOps 시장 : 제공별

  • 서론
  • 솔루션
  • 서비스

제7장 세계의 AIOps 시장 : 전개 모델별

  • 서론
  • 온프레미스
  • 클라우드

제8장 세계의 AIOps 시장 : 기업 규모별

  • 서론

제9장 세계의 AIOps 시장 : 최종 이용 업계별

  • 서론
  • 은행, 금융 서비스, 보험
  • 헬스케어
  • 소매
  • 커뮤니케이션과 테크놀러지
  • 정부
  • 제조
  • 미디어와 엔터테인먼트
  • 기타

제10장 세계의 AIOps 시장 분석 : 지역별

  • 서론
  • 북미
    • 미국
    • 캐나다
    • 멕시코
  • 남미
    • 브라질
    • 아르헨티나
    • 기타
  • 유럽
    • 영국
    • 독일
    • 프랑스
    • 스페인
    • 기타
  • 중동과 아프리카
    • 이스라엘
    • 사우디아라비아
    • 기타
  • 아시아태평양
    • 중국
    • 일본
    • 인도
    • 한국
    • 대만
    • 태국
    • 인도네시아
    • 기타

제11장 경쟁 환경과 분석

  • 주요 기업과 전략 분석
  • 신흥 기업과 고수익성 시장
  • 합병, 인수, 합의 및 협업
  • 벤더 경쟁력 매트릭스

제12장 기업 개요

  • IBM
  • Splunk
  • Micro Focus
  • HCL Technologies
  • BMC Software
  • Moogsoft
  • Resolve
  • GAVS Technologies
  • Sumo Logic
  • AppDynamics
KSM 22.03.18

The global AIOps market is projected to grow at a CAGR of 18.27% to reach US$5.477 billion by 2026, from US$1.692 billion in 2019. The Artificial Intelligence for IT Operations (AIOps) platform was developed from IT operations analytics (ITOA), and it refers to systems that use artificial intelligence and machine learning to automate processes for human use. AIOps platforms gather, interpret, and analyze huge amounts of IT data in real-time by using a variety of algorithms. AIOps is used with real-time data and helps a firm identify problems and resolve them with the use of various algorithms. It allows businesses and IT departments to get insight into their operations. As more applications, systems, and platforms must be kept running at top performance, information technology (IT) is being confronted with additional problems. The quantity of data created by both business and IT operations rises exponentially as an organization's complexity develops. AIOps analyzes the information from IT operations using artificial intelligence algorithms. The platform analyses the underlying cause of events in real-time and automates procedures to enhance responsiveness.

The market is expanding at a rapid pace throughout the world, owing to the rising demand for AI-based services for IT operations. The end-users growing desire to move more of their business operations to the cloud is driving up demand for AIOps platforms, which is propelling the market forward. End-user adoption of AIOps platforms is growing in tandem with exponentially expanding data quantities and ongoing expansion of end-to-end business applications, bolstering the market's growth. Because of the rising use of cloud-based solutions and the increasing complexity of IT infrastructure, the AIOps Platform is seeing remarkable growth. Another element driving market expansion is the ability to extend data and the requirement for predictive analysis. As the number of individuals working from home has grown, businesses have implemented work-from-home (WFH) policies that have moved the focus of information security from corporate infrastructure to cloud and virtualized infrastructure. According to the data given by the IBM Security Report 2020, around 54 percent of enterprises said they require remote working in response to Covid-19. As a result of these advancements, the desire for cloud-based solutions is expanding.

Growth Factors

Growing applications across the BFSI sector will boost the market growth

One of the major reasons for the growth of the global AIOps market is the growing applications of AIOps platforms in the BFSI sector. Employees, clients, and external agencies conduct a variety of periodic and aperiodic activities and transactions as part of banking operations. Because these operations are complicated, they must be closely monitored. AIOps is projected to enhance market growth throughout the forecast period by providing real-time information and automated issue resolution, among other things. For example, CA Technologies' AIOps product, CA Digital Experience Insights, assists financial businesses in resolving complex IT issues such as performance, capacity, and configuration. Banks must adopt a dependable IT operation management system to provide the highest possible service levels, principally to support internal processes and to give improved customer service. Furthermore, in their day-to-day IT operations, they are concentrating on maintaining maximum service efficiency. The market is projected to be driven by increasing regulatory standards, increasing use of cloud-based IT solutions, and expanding forms of online payment.

Restraints

Lack of awareness of AIOps and the growing complexities of the IT infrastructure will restrain the market growth

A major restraint in the growth of the global AIOps market is the lack of awareness among small and medium enterprises and the apprehension about the adoption of AIOps. Also, the market's growth is being stifled by factors such as the expanding complexity and dynamic nature of IT architecture, as well as the increasing number of changes in IT operations. These limitations have hindered the market growth for global AIOps during the forecast period.

Impact of COVID-19 on the AIOps Market

The COVID-19 pandemic has had a substantial impact on the world as a whole and has led to economic breakdown and loss of life. The COVID-19 impact on the global AIOps market has been positive owing to the exchange of volumes of data over data networks amid the course of the pandemic and the adoption of work from home practices. The deployment of wireless networking in recent years has further boosted the market growth of the global AIOps market. The work from home initiatives has led to companies being highly dependent on networking systems to control customer queries has led to the surging adoption of AIOps across various industry verticals. Several enterprises and companies running in the AIOps services are taking strategic initiatives to provide customers with the best services as they are entirely dependent on AIOps services during the pandemic. Several surveys have shown that employees have been more comfortable with work from measures. This development will lead to an increase in the adoption of AIOps services, worldwide, in the coming years.

Competitive Insights

The market leaders in the global AIOps market are: IBM, Splunk, Micro Focus, HCL Technologies, BMC Software, Moogsoft, Resolve, GAVS Technologies, Sumo Logic, and AppDynamics.

Segmentation:

The global AIOps market is segmented by component, offering, deployment model, enterprise size, end-user industry, and geography.

By Component

  • Data Collection and Analytics
  • Machine Learning and AI

By Offering

  • Solution
  • Services

By Deployment Model

  • On-premise
  • Cloud

By Enterprise Size

  • Small
  • Medium
  • Large

By End-User Industry

  • BFSI
  • Healthcare
  • Retail
  • Communication and Technology
  • Government
  • Manufacturing
  • Media and Entertainment
  • Others

By Geography

  • North America
    • USA
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • UK
    • Germany
    • France
    • Spain
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • Israel
    • Others
  • Asia Pacific
    • Japan
    • China
    • India
    • Indonesia
    • Taiwan
    • Thailand
    • Others

Table of Contents

1. Introduction

  • 1.1. Market Overview
  • 1.2. Covid-19 Scenario
  • 1.3. Market Definition
  • 1.4. Market Segmentation

2. Research Methodology

  • 2.1. Research Data
  • 2.2. Assumptions

3. Executive Summary

  • 3.1. Research Highlights

4. Market Dynamics

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis

5. Global AIOps Market by Component

  • 5.1. Introduction
  • 5.2. Data Collection and Analytics
  • 5.3. Machine Learning and AI

6. Global AIOps Market by Offering

  • 6.1. Introduction
  • 6.2. Solution
  • 6.3. Services

7. Global AIOps Market by Deployment Model

  • 7.1. Introduction
  • 7.2. On-premise
  • 7.3. Cloud

8. Global AIOps Market by Enterprise Size

  • 8.1. Introduction
  • 8.2. Small
  • 8.3. Medium
  • 8.4. Large

9. Global AIOps Market by End-User Industry

  • 9.1. Introduction
  • 9.2. BFSI
  • 9.3. Healthcare
  • 9.4. Retail
  • 9.5. Communication and Technology
  • 9.6. Government
  • 9.7. Manufacturing
  • 9.8. Media and Entertainment
  • 9.9. Others

10. Global AIOps Market Analysis, By Geography

  • 10.1. Introduction
  • 10.2. North America
    • 10.2.1. United States
    • 10.2.2. Canada
    • 10.2.3. Mexico
  • 10.3. South America
    • 10.3.1. Brazil
    • 10.3.2. Argentina
    • 10.3.3. Others
  • 10.4. Europe
    • 10.4.1. UK
    • 10.4.2. Germany
    • 10.4.3. France
    • 10.4.4. Spain
    • 10.4.5. Others
  • 10.5. Middle East and Africa
    • 10.5.1. Israel
    • 10.5.2. Saudi Arabia
    • 10.5.3. Others
  • 10.6. Asia Pacific
    • 10.6.1. China
    • 10.6.2. Japan
    • 10.6.3. India
    • 10.6.4. South Korea
    • 10.6.5. Taiwan
    • 10.6.6. Thailand
    • 10.6.7. Indonesia
    • 10.6.8. Others

11. Competitive Environment and Analysis

  • 11.1. Major Players and Strategy Analysis
  • 11.2. Emerging Players and Market Lucrativeness
  • 11.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 11.4. Vendor Competitiveness Matrix

12. Company Profiles

  • 12.1. IBM
  • 12.2. Splunk
  • 12.3. Micro Focus
  • 12.4. HCL Technologies
  • 12.5. BMC Software
  • 12.6. Moogsoft
  • 12.7. Resolve
  • 12.8. GAVS Technologies
  • 12.9. Sumo Logic
  • 12.10. AppDynamics
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