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

The telecom AIOps platforms market size was valued at USD 1.23 billion in 2025 and is estimated to expand from USD 1.84 billion in 2026 to reach USD 4.16 billion by 2031, at a CAGR of 17.72% during the forecast period (2026-2031). This report is segmented by Component (Platforms, and Services), Deployment Mode (On-Premises, Public Cloud, Private Cloud, and More), Application (Network Performance Management, Fault and Incident Management, and More), Organization Size (Large Enterprises, and SMEs), End User (Communications Service Providers, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Telecom AIOps Platforms Market Trends and Insights

5G, Open RAN, Edge, and Multi-Domain Network Complexity

The separation of radio access network functions has increased the number of systems that operations teams must coordinate. Distributed units, central units, radio units, and standardized Open RAN interfaces can involve multiple suppliers within a single network environment. Legacy network management systems were not designed to correlate this range of events at scale. 3GPP TS 23.288 defines the Network Data Analytics Function as part of analytics-led 5G core management, while leaving control choices to intelligence platforms outside the core function. That design gives AIOps suppliers a wider role in interpreting network data and supporting operational decisions. Standardized RIC interfaces from the O-RAN Alliance also make it more feasible to introduce automation across multi-vendor radio environments. The telecom AIOps platforms market benefits when operators need a shared operational view rather than separate tools for each network domain. These requirements are especially relevant as 5G deployments, edge sites, and virtualized functions expand simultaneously. The need is not simply to add more alerts, but to determine which alerts require action and which can be resolved through defined workflows.

Demand for Faster MTTR, Network Resilience, and SLA Compliance

Mean time to repair is increasingly linked to service obligations in enterprise connectivity contracts. A service interruption can create contractual exposure when private 5G and business network customers expect defined availability levels. This puts more focus on identifying faults before they affect users and on reducing the number of manual handoffs between teams. Indosat Ooredoo Hutchison and Huawei reported an 80% one-hop fault-closure rate in their AUTINOps deployment. They also reported a 15% reduction in mean time to repair and an improvement in availability from 99.3% to 99.7% across more than 17,000 islands. Documented operating results can shorten evaluation cycles for peer operators by demonstrating that automation can be applied beyond pilot settings. The telecom AIOps platforms market gains support from this shift toward measurable service outcomes. Network teams still need human review for complex and high-risk incidents, but repeatable fault patterns are better suited to automation. Faster triage also helps network operations centers and security operations centers coordinate during events with both performance and security implications.

Fragmented Telemetry, OSS/BSS Data Silos, and Inconsistent Data Quality

Many incumbent operators maintain operations and business support systems that were built through acquisitions, supplier choices, and successive network upgrades. The resulting data can differ in format, timing, and meaning between domains. An AIOps model trained on one event vocabulary may therefore classify alerts poorly when it receives data from another generation of technology. This weakens confidence in automated decisions and can slow a wider deployment. The problem is particularly serious when data records are incomplete or when asset, customer, and network records do not align. Operators need common data definitions and network knowledge structures before they can reliably scale automation. The telecom AIOps platforms market is constrained when these preparation tasks are treated as secondary to software selection. Vendors increasingly need to include data integration, model calibration, and knowledge graph work in deployment programs. Those services can improve the long-term value of a platform, but they also increase initial implementation effort. Clear data ownership and operating processes remain necessary after the platform is installed, as network changes can introduce new inconsistencies.

Other drivers and restraints analyzed in the detailed report include:

• Hybrid and Multi-Cloud Operations Expansion
• Telecom OPEX and Network Operations Labor Pressure
• Data Sovereignty, AI Governance, and Critical-Infrastructure Compliance

Segment Analysis

Platforms accounted for 56.43% of the telecom AIOps platforms market size in 2025. Operators favored integrated intelligence layers that can consolidate information from several operational tools. Telecom-specific offerings are built around 3GPP and O-RAN interfaces and can connect more deeply with OSS/BSS environments. General-purpose AIOps products are also extending into telecom through cloud partnerships and marketplace distribution. The first group can offer stronger domain alignment, while the second can benefit from broader enterprise software ecosystems. Both approaches must address data quality, alert correlation, and integration with existing workflows. TM Forum Open Digital Architecture compliance is becoming a screening factor for some Tier-1 operator evaluations. This supports suppliers that arrive with tested interfaces and documented interoperability. It also raises the importance of implementation capability, not only core platform features.

Services are projected to expand at an 18.21% CAGR from 2026 to 2031. Implementation specialists are needed to connect models with existing OSS/BSS stacks and to set operating rules for automated actions. Managed AIOps services can take responsibility for model maintenance, alert calibration, and updates to anomaly patterns. Consulting and integration services held the largest revenue share within the services category. Major operator implementations averaged USD 2.5 million to USD 4.0 million, reflecting the effort required to integrate into complex network environments. Custom model development is also relevant where operators in Japan, South Korea, and China develop proprietary training datasets. The telecom AIOps platforms industry depends on these services when operator teams cannot build and maintain models at the required speed. Service providers can also help transfer knowledge to internal teams and establish governance practices. This makes services a recurring part of platform value rather than a one-time installation activity.

Public cloud accounted for 47.88% of the telecom AIOps platform market share in 2025. Cloud-native delivery removes some on-premises infrastructure work and can make computing capacity easier to scale with network demand. It also allows operators to access software updates and shared development environments more easily. Nokia moved its autonomous operations stack to Amazon Web Services cloud infrastructure in June 2026, covering operations orchestration, assurance, unified inventory, and closed-loop automation. The company stated that commercial availability was expected later in 2026. The public cloud does not suit every workload because operators may have data residency and latency concerns. On-premises environments remain relevant in the Middle East, India, and parts of Asia-Pacific, where local control requirements are more significant. The choice depends on the sensitivity of data and the operational function being automated.

Hybrid cloud is projected to expand at a 19.41% CAGR from 2026 to 2031. This approach combines scalable computing resources with local controls for sensitive telemetry and selected network functions. It gives operators a way to move workloads gradually rather than shifting all functions to public infrastructure at once. NTT DOCOMO’s MantaRay AutoPilot deployment demonstrates that radio optimization can leverage public cloud resources while maintaining a broader hybrid operating model. Private cloud remains relevant for core network functions where governance, latency, or control policies limit public-cloud inference paths. The telecom AIOps platforms market is likely to favor suppliers that can operate consistently across these models. Portability matters because operator architecture can change as regulations, workloads, and cost structures evolve. A supplier that supports only one environment may face a narrower set of customer use cases. Hybrid designs also allow teams to test new AI functions while maintaining established controls for higher-risk workloads.

Complete Report Scope:

• By Component
  • Platforms
    • Domain-Centric Platforms
    • Domain-Agnostic Platforms
    • Telecom-Specific AIOps Platforms
    • General-Purpose AIOps Platforms
  • Services
    • Consulting Services
    • Integration and Implementation Services
    • Managed AIOps Services
    • Training, Support, and Maintenance Services
    • Custom AI Model Development Services
• By Deployment Mode
  • On-Premises
  • Public Cloud
  • Private Cloud
  • Hybrid Cloud
• By Application
  • Network Performance Management
  • Fault and Incident Management
  • Network and Security Operations
  • Infrastructure Management
  • Other Applications
• By Organization Size
  • Large Enterprises
  • Small and Medium Enterprises
• By End User
  • Communications Service Providers
    • Mobile Network Operators
    • Fixed-Line and Broadband Operators
    • Integrated Telecom Operators
    • Cable and Converged Operators
    • Data Center and Connectivity Providers
  • Managed Service Providers
  • Network Equipment Providers
  • System Integrators
  • Other End Users
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • South Korea
    • Rest of Asia-Pacific
  • Middle East
    • Saudi Arabia
    • United Arab Emirates
    • Rest of Middle East
  • Africa
    • South Africa
    • Egypt
    • Rest of Africa

Geography Analysis

North America is projected to account for 28.76% of the telecom AIOps platforms market size in 2025. The region combines a large base of platform vendors with Tier-1 carriers capable of supporting enterprise-grade deployments. These operators have the scale to invest in complex integrations and test new operating models. The vendor ecosystem also facilitates partnerships among equipment suppliers, cloud providers, observability firms, and service management specialists. In March 2026, TPG Telecom is expected to deploy Cisco’s Splunk platform to integrate network monitoring, IT operations, and cybersecurity tools within a unified observability and remediation framework. Active commercial programs and substantial technical capacity support the telecommunications AIOps opportunity in the region.

Europe has technically advanced operators; however, regulations such as the EU Digital Operational Resilience Act (DORA), NIS2, and the EU AI Act increase the importance of governance and control features. These requirements may slow the deployment of fully autonomous systems while increasing demand for platforms that offer auditability and human oversight. South America is also experiencing adoption beyond the largest carriers, as regional operators seek to reduce alarm noise and improve service resilience.

The Middle East is advancing through state-backed digital programs and investments in network modernization. Saudi Arabia and the United Arab Emirates are notable markets where data-localization requirements are driving demand for in-country inference capabilities and sovereign cloud configurations. Africa represents a longer-term opportunity, as ongoing infrastructure build-out may enable AI-native operations without the same level of legacy OSS technical debt. The telecom AIOps platforms market may develop differently across these regions due to significant variations in data regulations, network maturity, and procurement capacity.

Asia-Pacific is projected to expand at a CAGR of 19.17% during 2026-2031. High 5G deployment density, a large operator base, and pressure on operating margins are driving demand for more efficient network operations. NTT DOCOMO is expected to begin commercial operations of a generative AI-based mobile network maintenance agent system in February 2026. KDDI is also expected to begin operating a recovery-support AI agent that identifies failure causes in February 2026. China represents a major large-scale deployment environment, with China Mobile targeting Level 4 autonomous networks and China Telecom expected to deploy more than 900 AI agents.

List of Companies Covered in this Report:

• Nokia Corporation
• International Business Machines Corporation
• Cisco Systems, Inc.
• Ericsson
• ServiceNow, Inc.
• Dynatrace, Inc.
• Splunk LLC
• BMC Software, Inc.
• HCL Technologies Limited
• Tech Mahindra Limited
• NETSCOUT SYSTEMS, INC.
• Infovista SAS
• VIAVI Solutions Inc.
• Juniper Networks, Inc.
• Huawei Technologies Co., Ltd.
• Microsoft Corporation
• Amazon Web Services, Inc.
• Google LLC
• Elastic N.V.
• Datadog, Inc.
• PagerDuty, Inc.
• New Relic, Inc.
• Selector AI
• Grokstream

Additional Benefits:

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