首頁 > 市場調查報告書 > 通訊

人工智能

市場調查報告書

商品編碼

1629835

全球人工智慧 IT 營運平台市場 - 2024-2031

Global Artificial Intelligence For IT Operations Platform Market - 2024-2031

出版日期: 2024年12月30日 | 出版商:

DataM Intelligence | 英文 204 Pages | 商品交期: 最快1-2個工作天內

價格

※ 本網頁內容可能與最新版本有所差異。詳細情況請與我們聯繫。

簡介目錄

全球人工智慧IT營運平台市場規模在2023年達到15.9億美元，預計到2031年將達到85.9億美元，2024-2031年預測期間複合年成長率為23.47%。

AIOps 解決方案採用機器學習、巨量資料分析和自動化來最佳化 IT 營運，促進即時監控、異常識別和主動問題解決。 IT 環境日益複雜，加上對快速、精確解決問題的需求，加速了 AIOps 解決方案在銀行、醫療保健、零售和製造業等不同行業的實施。

國際商業實體的快速數位革命導致資料集日益複雜，需要大量的時間、費用和精力來進行資料處理。隨著 IT 營運經歷這種變化，IT 團隊遇到了管理複雜資料集以維持業務營運的問題。 NetBase Quid 在《2023 年人工智慧指數報告》中指出，根據各產業的合作與收購，2021 年人工智慧領域的年度企業投資預計將達到 1,196.6 億美元，2022 年將達到 771.7 億美元。

對數位創新的需求不斷成長，以及為提高解決方案的精度和效率而不斷增加的企業投資，推動了該領域對這些工具的需求。美國、加拿大和墨西哥的 Amazon Web Services, Inc.、IBM Corporation、Dynatrace LLC、BMC Software, Inc. 和 Dell Inc. 等著名 IT 營運工具提供商的人工智慧的存在將促進 AIOps 市場的成長預測期內北美。

動力學

轉變數位化營運

AIOps 正在透過增強 IT 營運來改變數位轉型，以滿足數位時代不斷成長的需求。這項創新技術透過最佳化後端流程和簡化複雜 IT 基礎架構的管理來提供無縫數位體驗。它有效地協調混合雲端生態系統內的基礎設施、應用程式和服務，確保有效性並提高客戶滿意度。

隨著全球企業在疫情後的遠距工作和協作環境中進行數位轉型，由於技術整合的複雜性，許多組織在實現其目標時遇到了困難。 AIOps 技術透過利用機器學習將營運資料情境化、自動解決問題並促進明智的決策來緩解這些挑戰。此解決方案最佳化轉型流程並促進有效的組織擴展。

IBM 2022 年的一項調查顯示，54% 的企業已經看到了人工智慧在各產業應用的好處。人工智慧的實施提高了 IT 或網路營運的效率 (53%)，透過提高效率減少開支並提高客戶滿意度 (48%)。

增強安全性和合規性

解決安全威脅和遵守監管標準的需求日益成長，正在推動 AIOps 平台的採用。隨著 IT 環境變得日益複雜和網路威脅，更先進的組織在檢測和回應安全漏洞同時保持法規遵循方面面臨挑戰。 AIOps 平台利用複雜的分析和機器學習演算法，透過檢查大量安全資料（包括日誌、事件和網路流量）來增強安全操作。

這些技術提供即時異常偵測和主動威脅識別，從而實現快速事件回應並降低違規風險。 AIOps 系統透過自動收集、分析和報告安全資料來增強合規性。他們提供持續的監督、創建審計追蹤並協助公司遵守行業要求。

AIOps 平台透過整合人工智慧和自動化來增強安全管理、保護重要資產並提高營運效率，使企業能夠有效地應對動態安全環境。 2024 年 2 月，Metra Group 宣布與印度 IT 營運安全人工智慧提供者 TechBridge Consultancy Services LLP 建立增值合作夥伴關係，利用先進的分析和 AI/ML 功能增強海灣合作理事會國家的數位轉型和安全性。

AIOps 演算法的不透明性

缺乏透明度削弱了決策過程中的信心和理解。在金融和醫療保健等受到嚴格監管的行業中，開放性的缺乏尤其令人擔憂，在這些行業中，責任和合規性至關重要。這些演算法的複雜性經常使其結果的驗證和解釋變得複雜，從而引發有關其可信度和公平性的問題。發展強大的可解釋性工具對於克服這些困難是必要的。

這些策略旨在闡明 AIOps 系統，為其決策過程提供透明的見解。組織可以透過促進開放來培養信任、保證監管遵守並增強對人工智慧生成建議背後推理的理解。在演算法複雜性和可解釋性之間實現平衡對於培養 AIOps 系統的信任至關重要。實現這種平衡不僅可以促進接受，還可以在人類判斷至關重要的領域加強問責制和開放性的基本原則。

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

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