According to the report published by Virtue Market Research, in 2022, the Global AIOps for Telecom Operations Market was valued at $558 million, and is projected to reach a market size of $9,594.58 million by 2030. Over the forecast period of 2023-2030, market is projected to grow at a CAGR of 42.7%.
A platform called artificial intelligence for information technology operations (AIOps) is intended to use AI and machine learning techniques to automate jobs and procedures with little to no human involvement. It makes use of a variety of algorithms to acquire, examine, and analyses data on IT operations in real-time to provide insights that may be put into practice. It may be installed using virtualized or software-defined resources on static physical systems, as well as on-premises, private, and hybrid cloud settings. AIOps employs performance monitoring technologies to gather and aggregate data, identify system problems and patterns, identify root causes, and report defects for quick reaction and correction. Additionally, it is utilised for network, log, and application monitoring as well as capacity optimization.
To increase network availability, capital efficiency, and cybersecurity assaults in cloud networks, AIOps serves as the core of the telecom operations innovation platform. AIOps is a crucial technology that significantly lowers operational costs and raises the value of brand equity and customer loyalty. The springboard for self-healing, resource hyper-scaling, and maximal automation is AI/ML. In this new environment, CSPs may raise employee-to-customer ratios from 1:1K to 1:50K, double the number of new services by 10, and launch new edge services in minutes as opposed to months. These operational performance measures are actual data from the best-run cloud hyperscale, fintech, and e-commerce companies rather than theoretical estimates. AIOps are used by telecom organizations to monitor the actions and transactions taken by staff, clients, and outside agencies, as well as to stop security breaches. Accordingly, the market is expanding as a result of the growing adoption of the work-from-home (WFH) trend by businesses. For improved information security when operating remotely, AIOps are deployed. Another element fueling growth is the numerous technological developments in cloud computing services. For the performance, network, and security management of critical business applications, organizations are increasingly using cloud-based solutions. AIOps also helps telecom companies to improve the infrastructure for delivering services more effectively. The market is anticipated to increase as a result of several other reasons, including major IT infrastructure upgrades, particularly in developing economies and intensive research and development (R&D) operations.
The AIOps Market was positively impacted by the COVID-19 outbreak. The declaration of a lockdown by the governments in this area led to a dramatic increase in the usage of the AIOps Platforms to respond to enquiries across several sectors, including healthcare, BFSI, retail, and e-commerce. Additionally, the AIOps platform helped several businesses create reliable remote work environments. Approximately 54% of businesses sought remote working in reaction to COVID-19, according to IBM Security Report 2020. The need for AIOps platforms is significantly increasing as a result of the pandemic's increased desire for cloud-based solutions.
AIOps aid in increasing operational efficiency which is a major reason for telecom companies adopting this technology
Artificial Intelligence for IT Operations (AIOps) is a platform that uses AI and research to improve IT operations and provide numerous facilities. This platform analyses the vast amounts of data amassed from various IT operations setups and devices that resolve the problems gradually. Additionally, it provides information collection strategies, insightful and demonstrative innovations, and the use of various informational components. The platform also offers a variety of IT operations disciplines together with cutting-edge analytical skills directly and indirectly. Artificial intelligence for IT operations is adaptable and centralized, which helps with analyzing astonishing amounts of information continuously offered by computerized algorithmic ML capacities. AIOps systems provide a number of layers that handle numerous capabilities for utilizing the innovations, including information assortment and capacity, representation, scientific instruments, and reconciliations with various applications. The aforementioned elements are boosting its acceptance and are likely to influence the market for AIOps platforms in the telecom sector.
The growth in the cloud platform is fueling the market expansion
The need for AIOps platforms has risen due to the growing adoption of cloud platforms by various telecom firms, which has boosted growth. The AIOps platform combines a variety of artificial intelligence techniques, including automation, machine learning, research, and others. Machine learning technology is now widely employed in a variety of systems that are used in the telecom industry, including recommender systems, image recognition systems, and voice recognition systems. The need for machine learning has risen as a result of this growing application. Additionally, the development of image recognition systems has improved system accuracy, which will raise the need for machine learning in the coming years.
Hesitancy by telecom operators in the adoption of AIOps solutions may impede the market growth
Comparatively speaking to other sectors of the economy, the telecommunications business has been quite sluggish to adopt operational automation. The financial results of CSPs have been directly impacted by this resistance to restructuring operations to benefit from low-cost machine intelligence. Traditional firms have been impacted by the tested AI-led business models used by creative cloud infrastructure, fintech, and digital commerce providers. In the telecom industry, hyperscale cloud service providers have seized market share in key communication domains including mobile content, cloud, and edge computing. Cloud providers can beat traditional telecom providers in terms of operational efficiency measures, thanks to the growing network disaggregation and the application of AI automation. This is partly because technology is now being used to replace labour, which has a high input cost, in corporate processes.
Market Size Available
2022 - 2030
2023 - 2030
By Offering, Application, Deployment Mode and Region
Various Analyses Covered
Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities
North America, Europe, APAC, Latin America, Middle East & Africa
Key Companies Profiled
APPDYNAMICS, BMC SOFTWARE, INC. , BROADCOM, HCL TECHNOLOGIES LIMITED
INTERNATIONAL BUSINESS MACHINES CORPORATION, MICRO FOCUS, MOOGSOFT
PROPHETSTOR DATA SERVICES, INC., RESOLVE SYSTEMS, SPLUNK INC. ,VMWARE, INC
This research report on the AIOps for Telecom Operations market has been segmented and sub-segmented based on Offering, Application, Deployment Mode and By Region.
Based on the offering, AIOps for the telecom market are segmented into Platform and Service. In 2021, the Artificial Intelligence for IT Operations (AIOps) platform for the telecom market was driven by the platform-providing segment, which accounted for over 85% of the worldwide revenue. AIOps suppliers provide organizations with dependable, adaptable, and cutting-edge platform experiences to give them a competitive edge in the marketplace. Its economic advantages, including improved decision-making, quicker digital transformation, effective data processing, and integrated agility, should be credited for this significant market share. Organizational demand for AIOps systems is significantly fueled by automation. Additionally, it makes correlation analytics deployment possible, which aids in detecting the primary source of IT infrastructure problems so that they may be appropriately fixed.
Application Performance Analysis
Network & Security Management
Based on the application, AIOps for the telecom market is segmented into Infrastructure Management, Application Performance Analysis, Real-Time Analytics, Network & Security Management and Others. With approximately 30.0% of worldwide sales, the real-time analytics application category dominated the market in 2021. The large share can be linked to real-time leader boards' growing use among organizations to gather competitive intelligence. Real-time analytics also offers businesses a data-driven method for locating, prioritizing, diagnosing, and addressing incidents or problems. Over the course of the projected period, it is predicted that the infrastructure management application segment would experience significant expansion. This expansion can be ascribed to the quick adoption of AI in demanding IT infrastructure tasks. For example, in January 2021, BMC Software, Inc., a worldwide information technology services and consulting company with headquarters in the United States, offers a variety of conventional cloud and IT operations solutions, mostly to large companies. A software product from the business, called TrueSight Infrastructure Management, integrates infrastructure monitoring, incident management, and operational analytics to provide IT, teams, with a consolidated view of IT infrastructures.
Based on the deployment, AIOps for the telecom market are segmented into Cloud and On-premise. With approximately 65.0% of the worldwide revenue share, the category of on-premises deployment models dominated the market in 2021. Due to the risk involved with installing AI models on the public cloud, telecom companies often opt to implement them on-premises. This high %age can be ascribed to on-premise IT operations' improved security and privacy. Edge analytics, which reduces the need for bandwidth, is also included in these solutions.
Over the projected period, it is predicted that the cloud deployment model sector would experience significant expansion. The removal of firewall constraints by cloud-based AIOps systems, which might impede access to an on-premises solution, is attributed to this increase. Platforms that are cloud-based and SaaS do away with overhead and maintenance expenses as well. In addition, cloud object storage services provide limitless virtual storage capacity, which eliminates the hardware's limitations on storage volume and scalability. For instance, Extra Hop, a leader in cloud-native network detection and response, declared in October 2021 that the scope of its Reveal(x) Advisor services had been increased to cover both threat detection and hunting and network assurance analysis.
The Asia Pacific
The Middle East
By region, the AIOps for Telecom Operations market is grouped into North America, Europe, Asia Pacific, Latin America, The Middle East and Africa. During the forecast period, North America is predicted to dominate the worldwide market for AIOps platforms due to the presence of several significant companies. The market for AIOps platforms is also being supported by growing government efforts for the local development of AIOPs systems. By introducing initiatives like the National Artificial Intelligence Research and Development and smart city programs throughout many districts, they are advancing the current IT infrastructure.
During the projection period, Asia Pacific is predicted to have considerable expansion. This can be attributable to the region's telecom sectors quickly adopting automation. Data analytics and other AI-based products and services have also been made possible by the rapid and massive data creation. For instance, to promote innovation in the AIOps development process, Micro Focus introduced brand-new software as a service platform in December 2021. This platform combines SaaS with full-stack AIOps. By offering observability, issue resolution, automation, and data translation capabilities, Micro Focus hopes to provide a "fast route" to a full-stack AIOps platform through their SaaS platform, dubbed Operations Bridge.
Some of the major players operating in the AIOps for Telecom Operations market include:
BMC SOFTWARE, INC.
HCL TECHNOLOGIES LIMITED
INTERNATIONAL BUSINESS MACHINES CORPORATION
PROPHETSTOR DATA SERVICES, INC.
PRODUCT LAUNCH- Global leader in digital transformation and communications MetTel declared in February 2022 that it will provide clients a managed secure access service edge solution powered by VMware SASE. The SASE solution will enable IT companies to more effectively deploy networking, cloud-based security, and edge compute capabilities to applications running at the edge.
PRODUCT LAUNCH- In August 2020, Rackspace Technology introduced Rackspace Fabric, which integrates the Moogsoft AIOps Platform that uses log, meter, trace, and alert data to apply artificial intelligence (AI) and machine learning (ML) to assist address IT events more quickly and proficiently. Through the use of machine learning to address IT issues, Rackspace customers will see greater uptime and fewer event notifications as a result of the integration into Rackspace Fabric.
PRODUCT LAUNCH- Broadcom introduced the most recent version of AIOps in December 2020. AIOps is an open platform with end-to-end observability, artificial intelligence, and machine learning that helps businesses achieve operational excellence. New AI/ML methods and configurable perspectives for more actionable data are now included in Broadcom's AIOps. A few of the new capabilities are full-stack observability, DX dashboards, service and alarm analytics, intelligent automation, capacity analytics, and continuous feedback loops.
Chapter 1. AIOPS FOR TELECOM OPERATIONS MARKET– Scope & Methodology
1.1. Market Segmentation
1.3. Research Methodology
1.4. Primary Sources
1.5. Secondary Sources
Chapter 2. AIOPS FOR TELECOM OPERATIONS MARKET – Executive Summary
2.1. Market Size & Forecast – (2023 – 2030) ($M/$Bn)
2.2. Key Trends & Insights
2.3. COVID-19 Impact Analysis
2.3.1. Impact during 2023 - 2030
2.3.2. Impact on Supply – Demand
Chapter 3. AIOPS FOR TELECOM OPERATIONS MARKET – Competition Scenario
3.1. Market Share Analysis
3.2. Product Benchmarking
3.3. Competitive Strategy & Development Scenario
3.4. Competitive Pricing Analysis
3.5. Supplier - Distributor Analysis
Chapter 4. AIOPS FOR TELECOM OPERATIONS MARKET- Entry Scenario
4.1. Case Studies – Start-up/Thriving Companies
4.2. Regulatory Scenario - By Region
4.3 Customer Analysis
4.4. Porter's Five Force Model
4.4.1. Bargaining Power of Suppliers
4.4.2. Bargaining Powers of Customers
4.4.3. Threat of New Entrants
4.4.4. Rivalry among Existing Players
4.4.5. Threat of Substitutes
Chapter 5. AIOPS FOR TELECOM OPERATIONS MARKET - Landscape
5.1. Value Chain Analysis – Key Stakeholders Impact Analysis
5.2. Market Drivers
5.3. Market Restraints/Challenges
5.4. Market Opportunities
Chapter 6. AIOPS FOR TELECOM OPERATIONS MARKET– By Offering
Chapter 7. AIOPS FOR TELECOM OPERATIONS MARKET – By Application
7.1. Infrasture Management
7.2. Application Performance Analysis
7.3. Real – Time Analytics
7.4. Network & Security Management
Chapter 8. AIOPS FOR TELECOM OPERATIONS MARKET – By Development Mode
8.2. On- Premise
Chapter 9. AIOPS FOR TELECOM OPERATIONS MARKET – By Region
9.1. North America
9.4. Latin America
9.5. The Middle East
Chapter 10. AIOPS FOR TELECOM OPERATIONS MARKET – By Companies
10.1. APP DYNAMICS
10.2. BMC SOFTWARE INC
10.4. HCL TECHNOLOGIES PVT LTD
10.5. INTERNATIONAL BUSSINESS MACHINE CORPORATION
10.6. MICRO FOCU
10.8. PEOPESTOR DATA SERVICES INC
10.9. RESOLVE SYSTMES INC
10.10. SPLUNCK INC
10.11. VMVARE INC
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