AIOps for Telecom Networks - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026-2031)

The AIOps for Telecom Networks Market size was valued at USD 5.14 billion in 2025 and is estimated to grow from USD 5.92 billion in 2026 to reach USD 12.07 billion by 2031, at a CAGR of 15.31% during the forecast period (2026-2031). This report is segmented by Offering (Platforms and Services), Deployment Model (On-Premises and Cloud-Based), Organization Size (Large Enterprises, and Small and Medium-Sized Enterprises), Application (Network Performance Management, Fault and Incident Management, and More), End-User (Mobile Network Operators, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global AIOps For Telecom Networks Market Trends and Insights

5G, Network Slicing, and Multi-Domain Complexity Reshape NOC Architecture

Standalone 5G networks require operators to manage service commitments across the radio, transport, and core domains, which often use separate vendor systems. Network slicing adds another layer because each slice requires performance controls tailored to its specific service-level agreement. The 3GPP Network Data Analytics Function provides a native data collection and inference interface within the 5G core, while the O-RAN Alliance RAN Intelligent Controller extends AI-based decision support into the radio domain. Together, these standards give the AIOps for telecom networks market a clearer technical route for deployment and vendor assessment. Operator programs have shown that AI agents can manage slicing policies across many enterprise customers and adjust resources in less than 50 milliseconds during traffic surges. A single cross-domain view reduces manual transfers between specialist network operations teams, while telecom-specific foundation models can improve the interpretation of combined radio, transport, core, and service data.

IoT and Edge Telemetry Volumes Force AI-Native Data Processing

IoT endpoints, edge nodes, and cloud-native network functions are generating more operational data than traditional network teams can manually review. Ericsson reported 2.6 billion broadband and critical IoT connections at the end of 2025, which increased the volume of continuous network telemetry. The AIOps for telecom networks market, therefore, depends on systems that can correlate signals from many network layers in real time. Edge-generated information often requires local filtering and semantic compression before it reaches a central inference layer. AWS has described telecom deployments in which edge-deployed small language models condense large raw telemetry streams into smaller diagnostic signals for cloud AI agents. This approach can lower backhaul requirements and shorten response times, particularly in geographically dispersed networks where centralized processing is less practical.

Legacy OSS and BSS Integration Costs Constrain AI Deployment Velocity

Legacy OSS and BSS systems are often customized for individual operators and can be difficult to connect with new AI tools. This challenge is more severe in multivendor networks, which require data adapters and normalization layers before telemetry can be interpreted consistently. Amdocs introduced aOS in February 2026 as an operating system designed to run on top of existing BSS and OSS stacks rather than replace them. That design reflects operator concerns about disruption during system integration. The AIOps for telecom networks market may see slower adoption among mid-tier operators without large internal integration teams. Cloud-native OSS designs aligned with TM Forum Open Digital Architecture can reduce future integration burdens. However, the installed base of older systems will continue to affect deployment speed and vendor selection over the forecast period.

Other drivers and restraints analyzed in the detailed report include:

• NOC Cost Reduction and MTTR Improvement Define AIOps ROI
• Predictive Service Assurance Becomes a Commercial Necessity for Operators
• Automated Remediation Introduces New Cybersecurity and Operational Risk Vectors

Segment Analysis

Platforms held 65.72% of the AIOps for telecom networks market share in 2025. Operators continue to favor integrated platforms that combine telemetry ingestion, model management, correlation, and closed-loop orchestration. This preference also reflects the need for carrier-grade reliability and telecom-specific operational knowledge. Platforms can include network ontologies and existing OSS connectors that general enterprise AIOps products lack. These capabilities help operators manage large volumes of alarms and performance data across several network domains. IBM Research demonstrated that telecom-focused foundation models can improve prediction accuracy for network data compared with conventional methods. This supports the position of specialized platforms within the AIOps industry for telecom networks. It also explains why operators often evaluate platforms as long-term architectural choices rather than isolated software purchases.

Services are projected to expand at a 17.24% CAGR from 2026 to 2031. This category includes implementation, platform customization, managed operations, and support for data preparation. Service demand remains closely tied to the complexity of brownfield network environments. Providers must often map legacy OSS and BSS data structures before an AI platform can operate reliably. Managed AIOps models are useful for operators that do not have dedicated AI operations teams. These models can offer more predictable outcome-based arrangements and reduce the need for internal infrastructure investment. The AIOps for telecom networks market will continue to require services, as implementation quality affects the reliability of any platform deployment. Services also help vendors build longer operator relationships after the initial platform sale.

On-premises deployment accounted for 54.63% of the AIOps market for telecom networks in 2025. This position reflected data sovereignty requirements, latency concerns, and long-standing operator preferences for local control. On-premises systems remain important where national rules limit cloud processing of network telemetry. They are especially relevant for state-affiliated operators in parts of the Asia-Pacific and the Middle East. Local deployment can also support highly sensitive workloads that require direct access to network infrastructure. These considerations sustain a meaningful installed base even as cloud options become more capable. The AIOps for telecom networks industry, therefore, continues to support both local and hybrid operating models. Hybrid designs can give operators flexibility while retaining control over high-risk or regulated data.

Cloud-based deployment is projected to expand at a 19.18% CAGR from 2026 to 2031. Elastic cloud infrastructure can support large-scale AI inference when traffic patterns change sharply within short periods. Nokia announced in June 2026 that its Autonomous Networks Fabric would be available on AWS infrastructure with applications for orchestration, assurance, and inventory management. Cloud delivery can also reduce upfront infrastructure requirements and speed software updates. European requirements around auditability and data residency are encouraging suppliers to provide sovereign cloud options alongside public cloud services. This is likely to preserve hybrid architectures for many operators. The AIOps for telecom networks market is moving toward cloud use without eliminating the need for on-premises control.

Complete Report Scope:

• By Offering
  • Platforms
  • Services
• By Deployment Model
  • On-Premises
  • Cloud-Based
• By Organization Size
  • Large Enterprises
  • Small and Medium-Sized Enterprises
• By Application
  • Network Performance Management
  • Fault and Incident Management
  • Network Security Management
  • Customer Experience Management
  • Infrastructure Management
  • Application Performance Analysis
  • Other Applications
• By End-User
  • Mobile Network Operators
  • Fixed and Broadband Operators
  • Integrated Communication Service Providers
  • Other End-Users
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Europe
    • United Kingdom
    • Germany
    • France
    • Spain
    • Italy
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia and New Zealand
    • Rest of Asia-Pacific
  • Middle East
    • Saudi Arabia
    • United Arab Emirates
    • Rest of Middle East
  • Africa
    • South Africa
    • Nigeria
    • Rest of Africa

Geography Analysis

North America held 31.13% revenue share in 2025, giving it the leading position in the AIOps for telecom networks market. Major United States operators have invested in AI-led network operations alongside wider 5G commercialization programs. The region also has a strong base of cloud AI providers that work with telecom vendors on integrated offerings. These conditions support the development of production-grade automation platforms. Canada is applying AIOps to rural and remote network management. Mexico is using the technology mainly to support automation during LTE-to-5G transitions. South America is led by Brazil, where operators are investing in fault correlation and predictive maintenance for multiband 5G networks. Adoption across South America also reflects the need to manage fiber and subsea infrastructure more efficiently.

Europe remains an important operating environment for the AIOps market in telecom networks. The United Kingdom, Germany, and France are advancing autonomous network programs using TM Forum frameworks. Deutsche Telekom deployed its RAN Guardian Agent in Germany during November 2025 and is expanding related programs to the Czech Republic and Croatia. The European Union AI Act has increased the need for governance, auditability, and documented controls. These requirements may favor established vendors that can show compliance with ETSI and 3GPP standards. Saudi Arabia and the United Arab Emirates are driving adoption in the Middle East through digital transformation programs focused on smart cities and critical connectivity. Africa remains at an earlier stage, with South Africa and Nigeria concentrating on fault management and performance optimization.

Asia-Pacific is projected to expand at a 17.78% CAGR from 2026 to 2031. China, India, South Korea, Japan, Australia, and New Zealand are increasing the use of AIOps for the telecom networks market as 5G networks scale. Huawei launched AUTINOps at MWC 2026 with more than 20 AI agents and reported over 80% risk-identification accuracy and above 90% diagnosis accuracy. Nokia is working with NTT DOCOMO on SMO-driven autonomy through MantaRay SON and AutoPilot trials. India offers high-volume telemetry conditions as standalone 5G coverage expands across a large mobile subscriber base. Australia and New Zealand are smaller but technically advanced markets that favor cloud-native deployments aligned with 3GPP and TM Forum standards.

List of Companies Covered in this Report:

• International Business Machines Corporation
• Cisco Systems, Inc.
• Nokia Corporation
• Telefonaktiebolaget LM Ericsson
• Amdocs Limited
• ServiceNow, Inc.
• Huawei Technologies Co., Ltd.
• Ciena Corporation
• Netcracker Technology Corporation
• Oracle Corporation
• Microsoft Corporation
• Google LLC
• ZTE Corporation
• NEC Corporation
• Samsung Electronics Co., Ltd.
• Tech Mahindra Limited
• Tata Consultancy Services Limited
• Infosys Limited
• Wipro Limited
• Radcom Ltd.
• Grokstream, Inc.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support