세계의 IT 운영 플랫폼용 인공지능(AI) 시장(2024-2031년)

Global Artificial Intelligence for IT Operations Platform Market reached US$ 1.59 billion in 2023 and is expected to reach US$ 8.59 billion by 2031, growing with a CAGR of 23.47% during the forecast period 2024-2031.

AIOps solutions employ machine learning, big data analytics and automation to optimize IT operations, facilitating real-time monitoring, anomaly identification and proactive issue resolution. The increasing intricacy of IT environments, along with the demand for expedited and precise problem resolution, has hastened the implementation of AIOps solutions across diverse sectors, including banking, healthcare, retail and manufacturing.

The swift digital revolution in international commercial entities has resulted in increasingly intricate datasets, necessitating substantial time, expense and effort for data processing. As IT operations undergo this change, IT teams encounter the issue of managing complex datasets to maintain business operations. As reported by NetBase Quid in the AI Index Report of 2023, the annual corporate investment in artificial intelligence was estimated at US$ 119.66 billion in 2021 and US$ 77.17 billion in 2022, based on collaborations and acquisitions across various industries.

The increasing demand for digital innovations and escalating corporate investments to improve the precision and efficiency of solutions are propelling the demand for these tools in the area. The presence of prominent artificial intelligence for IT operations tool providers, including Amazon Web Services, Inc., IBM Corporation, Dynatrace LLC, BMC Software, Inc. and Dell Inc., in US, Canada and Mexico will enhance the growth of the AIOps market in North America during the forecast period.

Dynamics

Transforming Digital Operations

AIOps is transforming digital transformation by enhancing IT operations to satisfy the growing demands of the digital age. This innovative technology enables the provision of seamless digital experiences by optimizing backend processes and streamlining the management of intricate IT infrastructures. It efficiently coordinates infrastructure, applications and services inside hybrid cloud ecosystems, guaranteeing effectiveness and improved customer satisfaction.

As global firms engage in digital transformation in the post-pandemic landscape of remote work and collaboration, numerous organizations encounter difficulties in realizing their goals due to the intricacies of technology integration. AIOps technologies mitigate these challenges by employing machine learning to contextualize operational data, automate problem resolution and facilitate informed decision-making. The solutions optimize transformation processes and facilitate effective organizational scaling.

A 2022 IBM survey indicated that 54% of enterprises have seen the benefits of AI application across all industries. The implementation of AI enhances the efficacy of IT or network operations (53%), decreases expenses through heightened efficiency and elevates customer happiness (48%).

Enhancing Security and Compliance

The increasing need to address security threats and comply with regulatory standards is driving the adoption of AIOps platforms. As IT environments become increasingly intricate and cyber threats more advanced organizations face challenges in detecting and responding to security breaches while maintaining regulatory compliance. AIOps platforms utilize sophisticated analytics and machine learning algorithms to enhance security operations by examining vast amounts of security data, including logs, events and network traffic.

The technologies provide real-time anomaly detection and proactive threat identification, enabling swift incident response and reducing the risk of breaches. AIOps systems enhance compliance by automating the collection, analysis and reporting of security data. They offer ongoing surveillance, create audit trails and assist firms in complying with industry requirements.

AIOps platforms increase security management, protect vital assets and improve operational efficiency by integrating AI and automation, enabling enterprises to efficiently traverse the dynamic security landscape. In February 2024, Metra Group announced a value-added partnership with TechBridge Consultancy Services LLP, an India-based provider of secure artificial intelligence for IT operations, to enhance digital transformation and security across GCC countries utilizing advanced analytics and AI/ML capabilities.

The Opacity of AIOps Algorithms

The lack of transparency eroding confidence and understanding in decision-making processes. The absence of openness is particularly alarming in heavily regulated industries like finance and healthcare, where responsibility and compliance are essential. The intricacy of these algorithms frequently complicates the validation and interpretation of their results, hence eliciting questions regarding their trustworthiness and equity. Developing robust interpretability tools is necessary to overcome these difficulties.

The strategies seek to elucidate AIOps systems, providing transparent insights into their decision-making processes. Organizations may cultivate trust, guarantee regulatory adherence and enhance comprehension of the reasoning behind AI-generated suggestions by promoting openness. Achieving a balance between algorithmic complexity and interpretability is essential for fostering trust in AIOps systems. Attaining this equilibrium not only fosters acceptance but also strengthens the essential principles of accountability and openness in sectors where human judgment is crucial..

Segment Analysis

The global artificial intelligence for IT operations platform market is segmented based on offering, application, deployment organization size, end-user and region.

Driving IT Efficiency With Platforms

AIOps platforms amalgamate many features, such as event correlation, anomaly detection and automated issue response, offering a comprehensive strategy for IT operations. This integration allows IT teams to enhance visibility and proactively oversee intricate hybrid and multi-cloud settings. Platforms enable the use of machine learning, big data analytics and automation, optimizing workflows and minimizing expenses. The capacity of these platforms to scale according to evolving IT requirements has increased their demand, as enterprises pursue solutions that facilitate digital transformation and enhance operational efficiency.

In March 2024, Visionet Systems Inc., a technology service provider, established a cooperation with Algomox, a provider of artificial intelligence for IT operations, to facilitate digital transformations in Visionet's ITOps operations. The incorporation of Algomox's AIOps platform into Visionet's managed cloud services automates intricate IT activities utilizing advanced AI technology, provides profound operational data insights and guarantees dependable service delivery.

Geographical Penetration

Advanced IT Infrastructure, Industry Demand, Real-Time Analytics and Digital Transformation in North America

North America comprises numerous prominent technology firms and sophisticated IT infrastructures, enabling the prompt implementation of cutting-edge AIOps solutions. The proliferation of numerous firms in diverse sectors, including finance, healthcare and retail, propels the necessity for effective IT operations and proactive incident management.

The escalating complexity of IT environments and the demand for real-time data analytics are driving the expansion of AIOps platforms in North America. Significant investments in research and development by major entities, coupled with a proficient staff, further enhance the United States' predominant share in the AIOps market. Moreover, the emphasis on digital transformation programs and cloud adoption among US enterprises amplifies the demand for scalable AIOps solutions.

Competitive Landscape

The major global players in the market include APPDYNAMICS, BMC Software, Inc., Broadcom Inc., HCL Technologies Limited, IBM Corporation, Micro Focus International plc, Dell Inc., ProphetStor Data Services, Inc., Splunk LLC and Thales.

Sustainability Analysis

Conventional IT operations encounter significant environmental issues, especially due to the energy consumption of data centers that frequently depend on non-renewable energy sources, resulting in elevated carbon emissions. The persistent need for hardware upgrades produces electronic waste, which presents environmental hazards if not disposed of properly. Manual IT processes are resource-intensive, resulting in inefficiencies and waste. As sustainability gains prominence, firms that use eco-friendly IT strategies not only diminish their environmental impact but also secure competitive advantages, enhance operational efficiencies and bolster future resilience against resource scarcity and stringent laws.

AIOps provides an effective solution to these difficulties by enhancing IT operations for sustainability. AIOps platforms utilize predictive analytics and automation to optimize resource allocation, reduce energy usage and prolong the longevity of IT infrastructure. AIOps tools can identify problems promptly, averting energy-consuming downtimes and superfluous resource expenditure. Moreover, by automating repetitive processes, AIOps diminishes the necessity for manual interventions, hence reducing operational inefficiencies.

Its capacity for dynamic resource adjustment via auto-scaling and self-healing mechanisms guarantees optimal resource usage, resulting in substantial energy savings. As AIOps platforms advance, they will be pivotal in advancing sustainability objectives, potentially minimizing e-waste and enhancing operations for more environmentally friendly IT practices, establishing AIOps as a fundamental element of future green IT endeavors.

Digital Transformation

AIOps (Artificial Intelligence for IT Operations) is emerging as a crucial facilitator of digital transformation across several industries. As enterprises increasingly depend on data-driven decision-making, AIOps offers essential solutions to enhance data management via automation. AIOps solutions facilitate the efficient management of data gathering, processing, analysis and visualization, enabling enterprises to discern critical insights in real time, hence maintaining competitiveness in a progressively intricate digital environment.

AIOps significantly enhances customer experience using sophisticated data analytics. Utilizing AI and machine learning enables organizations to acquire profound insights into client behavior, facilitating the customization of their products and services. AIOps facilitates product and service differentiation, bolstering brand loyalty and increasing income. Monitoring and observability capabilities guarantee a flawless customer engagement, proactively correcting issues and enhancing brand value.

AIOps mitigates interruptions by automating manual operations, hence decreasing bottlenecks and downtime. This automation promotes operational resilience and increases productivity across departments. AIOps' capacity to forecast possible problems with predictive algorithms enables enterprises to tackle challenges preemptively, hence ensuring seamless and uninterrupted operations.

By Offering

• Platform
• Domain-Centric
  • Monitoring-centric AIOps
  • ITSM centric-AIOps
  • Data-Lake centric-AIOps
• Domain-Agnostic
• Services
  • Professional Services
  • Managed Services

By Application

• Infrastructure Management
• Application Performance Analysis
• Real-Time Analytics
• Network & Security Management
• Others

By Deployment

• Cloud
• On-premises

By Organization Size

• Large Enterprises
• SMEs

By End-User

• IT & Telecom
• Retail & E-Commerce
• Energy & Utilities
• Media & Entertainment
• BFSI
• Healthcare & Life Sciences
• Government & Defense
• Transportation and Logistics
• Manufacturing
• Others

By Region

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Rest of Europe
• South America
  • Brazil
  • Argentina
  • Rest of South America
• Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • Rest of Asia-Pacific
• Middle East and Africa

Key Developments

• In September 2024, Vitria Technology, Inc., the architect of the VIA AIOps platform-an agile AI solution tailored for extensive operational intelligence-reported a significant increase in demand and customer acceptance. In the past year, Vitria Technology's AIOps platform facilitated a 60% enhancement in overall service availability, an 80% decrease in the time needed to handle service issues and 92% of incidents were identified prior to affecting consumers.
• In April 2024, BMC, a software solution provider, purchased Netreo, a provider of intelligent and secure IT network and application solutions, to enhance its leadership in observability and artificial intelligence for IT operations. BMC intends to enhance visibility into company operational performance across infrastructure, networks and apps via an open observability platform through this acquisition.
• In September 2023, Viavi Solutions Inc. established a relationship with Google Cloud to introduce NITRO AIOps, a cloud-based network intelligence and optimization solution. This collaboration sought to address significant difficulties faced by communication service providers (CSPs) and investigate new avenues for network optimization and intelligence.
• In January 2023, Interlink Software collaborated with Cisco to integrate their AIOps platform with AppDynamics. Through this integration, IT teams reduce the risk of avoidable outages and improve service availability, hence optimizing overall operational performance.

Why Purchase the Report?

• To visualize the global artificial intelligence for IT operations platform market segmentation based on offering, application, deployment organization size, end-user and region, as well as understand key commercial assets and players.
• Identify commercial opportunities by analyzing trends and co-development.
• Excel data sheet with numerous data points of the artificial intelligence for IT operations platform market-level with all segments.
• PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
• Product mapping available as excel consisting of key products of all the major players.

The global artificial intelligence for IT operations platform market report would provide approximately 78 tables, 80 figures and 204 pages.

Target Audience 2024

• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies

Table of Contents

1. Methodology and Scope

• 1.1. Research Methodology
• 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

• 3.1. Snippet by Offering
• 3.2. Snippet by Application
• 3.3. Snippet by Deployment
• 3.4. Snippet by Organization Size
• 3.5. Snippet by End-User
• 3.6. Snippet by Region

4. Dynamics

• 4.1. Impacting Factors
  • 4.1.1. Drivers
    • 4.1.1.1. Transforming Digital Operations
    • 4.1.1.2. Enhancing Security and Compliance
  • 4.1.2. Restraints
    • 4.1.2.1. The Opacity of AIOps Algorithms
  • 4.1.3. Opportunity
  • 4.1.4. Impact Analysis

5. Industry Analysis

• 5.1. Porter's Five Force Analysis
• 5.2. Supply Chain Analysis
• 5.3. Pricing Analysis
• 5.4. Regulatory Analysis
• 5.5. DMI Opinion

6. By Offering

• 6.1. Introduction
  • 6.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
  • 6.1.2. Market Attractiveness Index, By Offering
• 6.2. Platform*
  • 6.2.1. Introduction
  • 6.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 6.3. Domain-Centric
  • 6.3.1. Monitoring-centric AIOps
  • 6.3.2. ITSM centric-AIOps
  • 6.3.3. Data-Lake centric-AIOps
• 6.4. Domain-Agnostic
• 6.5. Services
  • 6.5.1. Professional Services
  • 6.5.2. Managed Services

7. By Application

• 7.1. Introduction
  • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 7.1.2. Market Attractiveness Index, By Application
• 7.2. Infrastructure Management*
  • 7.2.1. Introduction
  • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 7.3. Application Performance Analysis
• 7.4. Real-Time Analytics
• 7.5. Network & Security Management
• 7.6. Others

8. By Deployment

• 8.1. Introduction
  • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 8.1.2. Market Attractiveness Index, By Deployment
• 8.2. Cloud*
  • 8.2.1. Introduction
  • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 8.3. On-premises

9. By Organization Size

• 9.1. Introduction
  • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 9.1.2. Market Attractiveness Index, By Organization Size
• 9.2. Large Enterprises*
  • 9.2.1. Introduction
  • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 9.3. SMEs

10. By End-User

• 10.1. Introduction
  • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 10.1.2. Market Attractiveness Index, By End-User
• 10.2. IT & Telecom*
  • 10.2.1. Introduction
  • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 10.3. Retail & E-Commerce
• 10.4. Energy & Utilities
• 10.5. Media & Entertainment
• 10.6. BFSI
• 10.7. Healthcare & Life Sciences
• 10.8. Government & Defense
• 10.9. Transportation and Logistics
• 10.10. Manufacturing
• 10.11. Others

11. By Region

• 11.1. Introduction
  • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
  • 11.1.2. Market Attractiveness Index, By Region
• 11.2. North America
  • 11.2.1. Introduction
  • 11.2.2. Key Region-Specific Dynamics
  • 11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
  • 11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deloyment
  • 11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 11.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 11.2.8.1. US
    • 11.2.8.2. Canada
    • 11.2.8.3. Mexico
• 11.3. Europe
  • 11.3.1. Introduction
  • 11.3.2. Key Region-Specific Dynamics
  • 11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
  • 11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deloyment
  • 11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 11.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 11.3.8.1. Germany
    • 11.3.8.2. UK
    • 11.3.8.3. France
    • 11.3.8.4. Italy
    • 11.3.8.5. Spain
    • 11.3.8.6. Rest of Europe
• 11.4. South America
  • 11.4.1. Introduction
  • 11.4.2. Key Region-Specific Dynamics
  • 11.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
  • 11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deloyment
  • 11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 11.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 11.4.8.1. Brazil
    • 11.4.8.2. Argentina
    • 11.4.8.3. Rest of South America
• 11.5. Asia-Pacific
  • 11.5.1. Introduction
  • 11.5.2. Key Region-Specific Dynamics
  • 11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
  • 11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deloyment
  • 11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 11.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 11.5.8.1. China
    • 11.5.8.2. India
    • 11.5.8.3. Japan
    • 11.5.8.4. Australia
    • 11.5.8.5. Rest of Asia-Pacific
• 11.6. Middle East and Africa
  • 11.6.1. Introduction
  • 11.6.2. Key Region-Specific Dynamics
  • 11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
  • 11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deloyment
  • 11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 11.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

12. Competitive Landscape

• 12.1. Competitive Scenario
• 12.2. Market Positioning/Share Analysis
• 12.3. Mergers and Acquisitions Analysis

13. Company Profiles

• 13.1. APPDYNAMICS*
  • 13.1.1. Company Overview
  • 13.1.2. Product Portfolio and Description
  • 13.1.3. Financial Overview
  • 13.1.4. Key Developments
• 13.2. BMC Software, Inc.
• 13.3. Broadcom Inc.
• 13.4. HCL Technologies Limited
• 13.5. IBM Corporation
• 13.6. Micro Focus International plc
• 13.7. Dell Inc.
• 13.8. ProphetStor Data Services, Inc.
• 13.9. Splunk LLC
• 13.10. Thales

LIST NOT EXHAUSTIVE

14. Appendix

• 14.1. About Us and Services
• 14.2. Contact Us