AIOps for Telecom Operations Market Size (2024 – 2030)

The market size of AIOps for Telecom Operations, valued at USD 560 million in 2023, is anticipated to escalate to USD 6.7 billion by the conclusion of 2030. Across the forecast span from 2024 to 2030, the market is poised to burgeon at a compound annual growth rate (CAGR) of 42.7%.

Artificial Intelligence for IT operations (AIOps), a platform leveraging AI and machine learning methodologies to automate tasks and processes with minimal human intervention, is gaining prominence. It employs diverse algorithms to procure, scrutinize, and interpret real-time IT performance data, offering actionable insights. AIOps deployment options encompass built-in or software-defined infrastructure in standalone physical systems, as well as on-premise, private, and cloud environments. Utilizing performance monitoring technology, AIOps collates data, identifies issues and trends, pinpoints root causes, and reports anomalies for prompt response and recovery. Furthermore, it finds applications in network, logging, and application monitoring, along with capacity optimization.

At the core of telecom infrastructure platforms, AIOps is instrumental in bolstering network availability, financial performance, and fortification against cybersecurity threats in cloud networks. Recognized as a pivotal technology, AIOps drives down operational costs while augmenting equity value and customer allegiance. AI/ML serves as a catalyst for self-healing capabilities, hyper-scalability of resources, and maximal automation, enabling Communication Service Providers (CSPs) to scale up services to clients exponentially, hasten the launch of new services, and introduce innovative offerings swiftly. The proliferation of AIOps is spurred by heightened acceptance of remote work practices, necessitating enhanced information security measures. Additionally, technological advancements in cloud services contribute to market expansion as organizations increasingly leverage cloud-based solutions for performance, network, and security management of critical business applications. Moreover, significant enhancements in IT infrastructure, propelled by economic development and intensive research and development (R&D) efforts, further drive market growth.

Key Market Insights:

The AIOps market for telecom services is undergoing a paradigm shift due to the escalating complexity of telecom networks, compounded by the advent of 5G, IoT devices, and advanced services. AIOps solutions play a pivotal role in managing and enhancing network performance, offering proactive issue resolution through predictive analytics to preemptively identify and address potential disruptions. Emphasis is placed on operational streamlining achieved through task automation, particularly in routine network monitoring and incident management. Real-time analysis assumes a central role, facilitating swift decision-making amidst dynamic network conditions. Seamless integration with existing systems is imperative for successful implementation, ensuring smooth transitions sans disruptions to ongoing operations. AIOps aids in cost reduction by optimizing resource allocation and forestalling costly incidents, while fortifying security measures through enhanced monitoring and compliance. The market landscape is characterized by a diverse array of vendors, comprising established IT enterprises and specialized AIOps providers offering tailored solutions. Leveraging machine learning and predictive analytics, AIOps harnesses historical data to forecast potential challenges, rendering it indispensable for telcos navigating evolving network configurations.

AIOps for Telecom Operations Market Drivers:

The proliferation of AIOps is propelled by its efficacy in enhancing operational efficiency, a primary motivator for adoption among telecom companies.

Artificial Intelligence for IT Operations (AIOps) represents a platform harnessing AI and analytics to optimize IT operations and cater to diverse clientele. The platform ingests vast datasets sourced from myriad IT service providers and tools, facilitating gradual issue resolution. Additionally, it furnishes a data aggregation framework, innovative features, and diverse analytical capabilities, directly and transparently. AIOps is characterized by its flexibility and centralization, enabling continuous analysis of copious data streams through the computational prowess of ML algorithms. AIOps systems offer multifaceted capabilities across diverse domains, encompassing data processing and visualization, predictive modeling, and compliance adherence, among others. The aforementioned factors drive adoption and are poised to shape the trajectory of AIOps platform market in the telecom sector.

Cloud Platform Growth Fuels Rapid Market Expansion:

The burgeoning adoption of cloud platforms by various telecom entities underscores the heightened demand for AIOps platforms, propelling market expansion. AIOps platforms amalgamate diverse AI techniques, including automation, machine learning, and search functionalities. Machine learning technology finds widespread application across multiple domains within the media industry, encompassing streaming, image recognition, and voice recognition systems. The growing application landscape underscores the escalating significance of machine learning. Furthermore, advancements in image recognition systems bolster system accuracy, further amplifying the relevance of machine learning in the forthcoming years.

AIOps for Telecom Operations Market Restraints and Challenges:

Lagging adoption of AIOps solutions among telecom operators poses a challenge to market growth.

Compared to other sectors, the telecommunications industry has been relatively sluggish in embracing automation. The resistance to embracing transformative technologies has directly impacted CSPs' financial performance. Conventional business models have been disrupted by AI-driven paradigms prevalent in natural cloud infrastructures, fintech, and digital business sectors. Cloud service providers have seized market share in critical communication domains, including mobile content, cloud computing, and edge computing, outperforming traditional telecom providers in operational metrics owing to enhanced network scalability and AI-driven automation applications. This transition partly stems from the substitution of labor-intensive processes with technology-driven solutions, thereby curtailing input costs.

AIOps for Telecom Operations Market Opportunities:

The AIOps market for telecom operations is replete with opportunities driven by the integration of transformative technologies. The advent of 5G, coupled with the proliferation of IoT devices, fuels demand for advanced network management solutions. AIOps, with its predictive analytics and automation capabilities, empowers telecom operators to optimize networks, facilitate seamless 5G deployment, and manage IoT devices efficiently. Enhanced issue identification and resolution enhance network reliability, a critical competitive advantage. Furthermore, AIOps streamlines operations through task automation, paving the way for cost savings. Data security and AIOps situational awareness assume paramount importance in addressing critical concerns within the telecommunications sector. Effective time management facilitates expedited decision-making, fosters economies of scale, and enables personalized service offerings, thereby unlocking diverse avenues for innovation and growth in the telecommunications landscape.

Segmentation of the AIOps for Telecom Operations Market: By Offering

• Platforms
• Services

In terms of offerings, the AIOps for the telecom market is categorized into platforms and services. As of 2023, platform providers contributed to over 85% of the global revenue in AI operations for IT operations (AIOps) in the telecommunications sector. These providers furnish organizations with robust, scalable, and seasoned platforms to gain a competitive edge in the market. The economic advantages stemming from this substantial market share are anticipated to include enhanced decision-making, accelerated digital transformation, streamlined data processing, and embedded functionalities. The demand for AIOps systems within organizations is largely propelled by automation needs. Moreover, it facilitates interactive analysis importation, aiding in the pinpointing of IT infrastructure issues for effective resolution.

Segmentation of the AIOps for Telecom Operations Market: By Application

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

In terms of application, the AIOps for telecom market is segmented into infrastructure management, application performance analysis, real-time analysis, network management and security, and others. The real-time analysis category is poised to dominate the market, capturing a 30.0% share of the global market. This significant share can be attributed to leveraging existing resources alongside expanding teams to garner competitive insights. Real-time analysis empowers businesses with a data-centric approach to identifying, prioritizing, diagnosing, and resolving problems or issues. During the forecast period, substantial growth is expected in the resource management sector, driven by the rapid adoption of AI to meet the demands of IT infrastructure.

Regional Analysis of the AIOps for Telecom Operations Market

• North America
• Asia-Pacific
• Europe
• South America
• Middle East and Africa

The AIOps for telecom services market is regionally segmented into North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa. North America is anticipated to dominate the global AIOps platform market during the forecast period, primarily due to the presence of numerous prominent companies. Additionally, growing governmental initiatives for regional development of AIOps systems further bolster the AIOps platform market. Initiatives such as the National Intelligence Research and Development Program and the Smart City program in various regions are currently fostering IT infrastructure development. Significant expansion is projected in the Asia-Pacific region during the forecast period, attributed to the region's swift adoption of AI across multiple sectors. The availability of data analysis and other AI-based products and services is facilitated by the rapid generation of data on a large scale.

Impact of COVID-19 on the AIOps Market:

The AIOps market has been significantly impacted by the COVID-19 pandemic. Government-imposed lockdowns have led to a substantial surge in the utilization of AIOps platforms across various industries, including healthcare, BFSI, retail, and e-commerce, to address challenges. Moreover, AIOps platforms have facilitated the establishment of reliable remote work environments for many enterprises. According to the IBM Security 2020 report, approximately 54% of businesses resorted to remote work in response to COVID-19, further driving the demand for AIOps platforms, especially cloud-based solutions.

Recent Trends and Developments:

The AIOps landscape for Telecom Operations is witnessing dynamic advancements, focusing on harnessing artificial intelligence to enhance efficiency and performance. Recent trends encompass an increased emphasis on AI-driven predictive maintenance to proactively tackle network issues, particularly with the expansion of 5G networks. Integration with edge computing is gaining traction, ensuring real-time analytics at the network edge. Security features are evolving to combat cybersecurity threats, with advanced threat detection and compliance monitoring becoming integral. The industry is progressing towards autonomous operations, with AIOps systems taking on more decision-making processes independently. Cloud-native AIOps solutions are expected to offer greater scalability and flexibility, aligning with the broader trend of cloud adoption. The latest trends underscore the industry's commitment to optimizing Telecom Operations through cutting-edge AIOps solutions.

Key Players:

1. Appdynamics
2. Bmc software, inc.
3. Broadcom
4. Hcl technologies limited
5. International business machines corporation
6. Micro focus
7. Moogsoft
8. Prophetstor data services, inc.
9. Resolve systems
10. Splunkinc.
11. Vmware, inc.

• In February 2022, MetTel, a global digital transformation and communications leader, announced its provision of a fully managed secure access service solution powered by VMware SASE. This move aims to enable IT organizations to deploy networking, cloud security, and computing capabilities to applications operating at the edge.
• In August 2022, Rackspace Technologies introduced Rackspace Fabric, which integrates MoogsoftAIOps systems. These systems utilize log, measure, trace, and alert data to apply artificial intelligence and machine learning, aiding in faster and more efficient IT program management.