Agentic Artificial Intelligence in Telecommunications and Network Management Market

What is the Agentic Artificial Intelligence in Telecommunications and Network Management Market forecast to be worth by 2036?

The market is projected to reach USD 61.8 billion by 2036.CAGR of 19.5%

• The Agentic Artificial Intelligence in Telecommunications and Network Management market reached USD 8.7 billion in 2025.
• Demand is forecast to increase from USD 10.4 billion in 2026 to USD 61.8 billion by 2036.
• The market is forecast to expand at a CAGR of 19.5% from 2026 to 2036.

What are the defining numbers behind Agentic Artificial Intelligence in Telecommunications and Network Management Market growth?

An absolute dollar opportunity of USD 51.4 billion is expected between 2026 and 2036.

• Demand Drivers in the Market
  • The main driver is the widening gap between network complexity and available engineering attention. Operators now manage radio and core domains with cloud platforms and external service dependencies, creating more conditions than teams can monitor manually.
  • Agentic systems add value when they coordinate tools across operational tasks instead of producing a standalone recommendation. Buyers respond by funding operations agents and data connectors that shorten diagnosis, and they can redirect scarce specialists toward policy design and exceptional incidents.
  • Industry bodies are documenting practical use cases. The GSMA AI Use Case Library documented uses for AI in energy management and service optimization in March 2025, and the Global Coalition on Telecommunications issued principles on AI adoption in January 2025.
  • Standards provide a reference for closed-loop automation. The ETSI Zero-touch Network and Service Management framework gives operators a standards-based approach for intent and automation, and ITU-T published requirements for deploying and assessing generative AI models in telecom networks in March 2025.
  • Vendors are shipping network agents. Cisco introduced AgenticOps in June 2025 to combine agents with network telemetry and domain automation, Google Cloud described its Autonomous Network Operations framework in June 2025, and Nokia upgraded its autonomous networks portfolio with agentic AI in June 2026.
  • Public investment is expanding the funding base. NTIA reported in May 2025 that 94 applications sought nearly USD 3 billion for software-led wireless innovation in the United States, and South Korea’s 2025 MSIT budget plan funds network AI research.
• Key Segments Analyzed
  • Network Operations Agents anchor the AI Agent Function segment with a 38.0% share in 2026, because fault triage and service assurance are frequent workflows with observable outcomes.
  • Network Performance Optimization leads the Network Application segment, taking 36.0% of demand in 2026, as operators can tie agent recommendations to throughput and service-level measures.
  • Telecommunication Service Providers is the dominant End-use Segment at 48.0% in 2026, reflecting the scale of operator investment in network automation.
  • Tier-1 Telecom Operators lead the Organization Type segment with a 45.0% share in 2026, because they can spread integration costs across large network footprints.
  • Cloud-native AI Agents lead the Deployment Architecture segment at 47.0% in 2026, as operators need elastic inference and shared context across distributed applications.
• Analyst Opinion at Fact.MR
  • Shambhu Nath Jha, Principal Consultant at Fact.MR, states: “Telecom operators are moving from standalone AI recommendations to agents that act inside network operations, and Network Operations Agents already hold 38.0% of the market in 2026 because fault triage and service assurance produce measurable, repeatable outcomes. The ETSI Zero-touch framework and ITU-T guidance give operators a standards-based approval path, while cloud-native deployment makes agents practical across distributed networks. But fragmented telemetry and strict change controls limit autonomous action in production environments. Modular agents with policy enforcement, that can extend automation from one domain into end-to-end operations under human approval, will capture the largest share of operator spending.”
• Strategic Implications
  • Network equipment vendors should connect agent layers to radio and core telemetry, because domain context and installed operations software are the entry point for operator trust.
  • Compute and cloud providers should deliver elastic inference with workload-placement, identity, and audit controls, since operators require consistent governance across clouds and edge locations.
  • Vendors should design modular agents with policy enforcement that can extend automation from one domain into end-to-end operations, generating recurring revenue across high-usage segments.
  • Channel and service investment should follow the fastest-growing country markets, including the USA, UK, and South Korea, while adapting to local testbeds and regulation.
  • Providers should invest in data-layer assembly and change controls, because buyers purchase an operating model that joins compute and network context with integration support rather than an isolated agent.

How does the Agentic Artificial Intelligence in Telecommunications and Network Management Market break down by segment?

The market is structured across five analytical dimensions plus region. Network Operations Agents leads the AI Agent Function segment. Network Performance Optimization leads the Network Application segment. Telecommunication Service Providers leads the End-use Segment segment. Tier-1 Telecom Operators leads the Organization Type segment. Cloud-native AI Agents leads the Deployment Architecture segment. Regionally, USA, UK, South Korea, Japan, Germany, Canada, Australia anchor the demand base.

Why do Network Operations Agents lead AI Agent Function?

Network Operations Agents is projected to account for a 38.0% share in 2026.

Network Operations Agents lead because fault triage and service assurance are frequent workflows with observable outcomes. These agents can combine alarms and topology data, then suggest a sequence of checks or actions. The ETSI Zero-touch Network and Service Management framework gives operators a standards-based reference for intent and closed-loop automation, reducing the distance between an agent pilot and an existing operations process. Daily use produces repeatable feedback on false alarms and action quality, which supports renewal and expansion into adjacent assurance tasks. Cisco introduced AgenticOps in June 2025 to combine agents with network telemetry and domain automation across operations tasks.

Why does Network Performance Optimization lead Network Application?

Network Performance Optimization is projected to account for a 36.0% share in 2026.

Network Performance Optimization leads because operators can tie agent recommendations to throughput and service-level measures. Traffic engineering and quality monitoring provide continuous data that supports iterative learning under policy constraints. The ITU-T guidance on generative AI in telecom networks places assessment and deployment requirements around model use in network environments, so buyers can evaluate accuracy and operational risk against a defined task. Optimization programs often expand before fully autonomous remediation because recommendations can first pass through engineering approval, a staged path that protects service quality while building an evidence base for later automation.

Why do Telecommunication Service Providers lead End-use Segment?

Telecommunication Service Providers is projected to account for a 48.0% share in 2026.

Telecommunication service providers lead the End-use Segment because they operate the networks where reliability, capacity, and customer experience are measured directly against revenue. They manage multi-vendor radio and core domains, run cloud-native operations platforms, and face constant traffic and spectrum pressure, making them the earliest and largest buyers of agents that shorten fault isolation and capacity decisions. Their engineering teams are the ones adopting the ETSI Zero-touch framework and ITU-T guidance, and they fund the data-layer integration that agents depend on. Google Cloud described its Autonomous Network Operations framework in June 2025 with agents for radio and cross-domain operations, illustrating the operator-centric pattern.

Why do Tier-1 Telecom Operators lead Organization Type?

Tier-1 Telecom Operators is projected to account for a 45.0% share in 2026.

Tier-1 operators can spread integration costs across large subscriber and network footprints, and their scale creates the strongest need for cross-domain coordination. These organizations can fund data engineering and policy design before the benefits appear and can negotiate platform support across several vendors, so a common orchestration layer serves more than one business unit. Smaller operators face the same operational pressure but often prefer managed services or predefined agents because specialist staffing and model governance carry a higher cost per network element. NTIA reported in May 2025 that 94 applications sought nearly USD 3 billion for software-led wireless innovation in the United States, underscoring the scale of Tier-1-led network modernization.

Why do Cloud-native AI Agents lead Deployment Architecture?

Cloud-native AI Agents is projected to account for a 47.0% share in 2026.

Cloud-native AI Agents lead because telecom teams need elastic inference and shared context across distributed applications. Containerized deployment fits the architecture of newer core and operations platforms, and public cloud supports fast access to models while private cloud preserves control over sensitive telemetry. Hybrid patterns connect those environments with edge execution. The GSMA AI Transformation Blueprint identifies cloud-native infrastructure and data governance as core conditions for telecom AI. Buyers still require workload placement rules before agents can act on production systems, plus a consistent identity and audit model across clouds and edge locations. NVIDIA launched AI Aerial in September 2024 to support AI-RAN development across accelerated computing infrastructure.

What is accelerating Agentic Artificial Intelligence in Telecommunications and Network Management Market adoption, and what is holding it back?

Drivers Impact Analysis

Restraints Impact Analysis

Which countries are scaling the Agentic Artificial Intelligence in Telecommunications and Network Management Market fastest?

• The United States leads the pace of expansion on the strength of software-led wireless funding, with NTIA reporting in May 2025 that 94 applications sought nearly USD 3 billion for wireless innovation and related integration work.
• The United Kingdom is scaling as operators connect AI automation to concentrated resilience requirements, supported by Ofcom’s network and service resilience guidance issued in September 2024.
• South Korea is advancing through state-backed testbeds and research funding, with the 2025 MSIT budget plan supporting network AI and communications research.
• Japan is growing through interoperability and trusted-control programs, supported by NICT’s collaboration with Fraunhofer HHI on the Optical Testbed Dataspace launched in March 2025.
• Germany is expanding as policy accelerates network build-out and digital transformation, with the Federal Ministry for Digital Transformation issuing a telecommunications network build-out acceleration program in May 2025.
• Canada is building demand as the federal government strengthens the telecommunications ecosystem, with ISED announcing support in December 2024.
• Australia is adopting as operators improve network and service processes, with the ACMA proposing amendments to the Telecommunications Consumer Complaints Handling Industry Standard in February 2025.

Country-wise CAGR Forecast (2026-2036)

What is driving the Agentic Artificial Intelligence in Telecommunications and Network Management Market in the USA?

USA is projected to register a 21.2% CAGR through 2036, supported by software-led wireless funding and large operator estates.

American operators are investing in software-defined networks and wireless innovation. NTIA reported in May 2025 that 94 applications sought nearly USD 3 billion for software-led wireless innovation and related integration work, giving U.S. operators and vendors a strong funding signal for agentic network automation.

What is driving the Agentic Artificial Intelligence in Telecommunications and Network Management Market in the UK?

The UK is projected to register a 20.5% CAGR through 2036, supported by concentrated resilience requirements and regulated service outcomes.

British operators connect AI automation to concentrated resilience expectations. Ofcom issued network and service resilience guidance in September 2024, and the Global Coalition on Telecommunications set out AI adoption principles in January 2025, providing a regulatory reference that supports governed deployment of network agents.

What is driving the Agentic Artificial Intelligence in Telecommunications and Network Management Market in South Korea?

South Korea is projected to register a 19.8% CAGR through 2036, supported by state-backed testbeds and research funding.

Korean operators and vendors benefit from state-backed testbeds and research funding. The 2025 MSIT budget plan supports network AI and communications research, and the country’s advanced 5G and 6G programs give suppliers a dense environment for validating agentic automation.

What is driving the Agentic Artificial Intelligence in Telecommunications and Network Management Market in Japan?

Japan is projected to register a 19.1% CAGR through 2036, supported by interoperability programs and trusted control.

Japanese operators place strong weight on interoperability and trusted control. NICT launched the Optical Testbed Dataspace with Fraunhofer HHI in March 2025, providing a shared research environment for network AI, and Japanese vendors are aligning agent deployments with the country’s reliability expectations.

What is driving the Agentic Artificial Intelligence in Telecommunications and Network Management Market in Germany?

Germany is projected to register an 18.3% CAGR through 2036, supported by network build-out acceleration and digital transformation.

German policy is accelerating network build-out and digital transformation. The Federal Ministry for Digital Transformation issued a telecommunications network build-out acceleration program in May 2025, which expands the modern infrastructure base where operators deploy agentic automation.

What is driving the Agentic Artificial Intelligence in Telecommunications and Network Management Market in Canada?

Canada is projected to register a 17.7% CAGR through 2036, supported by federal support for the telecommunications ecosystem.

Canadian operators are modernizing with federal support. ISED announced in December 2024 that the federal government would strengthen Canada’s telecommunications ecosystem, providing a policy backdrop for network AI and automation investment.

What is driving the Agentic Artificial Intelligence in Telecommunications and Network Management Market in Australia?

Australia is projected to register a 17.0% CAGR through 2036, supported by network and service process improvements.

Australian operators are improving network and service processes alongside regulatory engagement. The ACMA proposed amendments to the Telecommunications Consumer Complaints Handling Industry Standard in February 2025, and operators are using AI agents to improve service assurance within those expectations.

Who leads the Agentic Artificial Intelligence in Telecommunications and Network Management Market?

Competition is organized around three linked roles. Compute and cloud providers supply models, agent tooling, data services, and scalable inference. Network equipment companies connect those capabilities to radio and core controls, with domain telemetry and installed operations software as their advantage. Service firms assemble the data layer and change controls around a chosen platform and take responsibility for workflow redesign and adoption.

AI compute and cloud agent platforms: NVIDIA Corporation, Microsoft Corporation, Google LLC, IBM Corporation, and Amazon Web Services, Inc. Network infrastructure and autonomous operations: Cisco Systems, Inc., Ericsson AB, Nokia Corporation, and Huawei Technologies Co., Ltd. Integration and managed transformation: Accenture plc and Wipro Limited.

Which companies are the key providers?

Key companies profiled in the Agentic Artificial Intelligence in Telecommunications and Network Management market include NVIDIA Corporation, Microsoft Corporation, Google LLC, IBM Corporation, Amazon Web Services, Inc., Cisco Systems, Inc., Ericsson AB, Nokia Corporation, Huawei Technologies Co., Ltd., Accenture plc, and Wipro Limited.

• NVIDIA Corporation
• Microsoft Corporation
• Google LLC
• IBM Corporation
• Amazon Web Services, Inc.
• Cisco Systems, Inc.
• Ericsson AB
• Nokia Corporation
• Huawei Technologies Co., Ltd.
• Accenture plc
• Wipro Limited

Bibliography

• International Telecommunication Union. (2025, March). Potential requirements and methodology for deploying and assessing generative AI models in telecom networks.
• European Telecommunications Standards Institute. (2023, October 5). ETSI’s Zero-touch Network and Service Management group renewed for two years.
• GSMA. (2025, March 20). How the GSMA AI Use Case Library is helping telecoms deploy AI at scale.
• Global Coalition on Telecommunications. (2025, January 16). Principles on AI adoption in the telecommunications industry.
• National Telecommunications and Information Administration. (2025, May 8). More than 90 applications requesting nearly USD 3 billion submitted to the Wireless Innovation Fund’s third round.
• Ofcom. (2024, September 5). Network and service resilience guidance.
• Ministry of Science and ICT, Republic of Korea. (2024, August). 2025 MSIT budget plan.
• National Institute of Information and Communications Technology. (2025, March 31). NICT and Fraunhofer HHI launch Optical Testbed Dataspace.
• Federal Ministry for Digital Transformation and Government Modernisation, Germany. (2025, May 28). Accelerating telecommunications network build-out.
• Innovation, Science and Economic Development Canada. (2024, December 9). Federal government strengthens Canada’s telecommunications ecosystem.
• Australian Communications and Media Authority. (2025, February). Proposed amendments to the Telecommunications Consumer Complaints Handling Industry Standard.
• NVIDIA Corporation. (2024, September 18). NVIDIA AI Aerial launches to transform wireless networks with AI-RAN.
• Cisco Systems, Inc. (2025, June 10). Network operations for the AI age.
• Accenture plc. (2026, February 24). Accenture acquires advanced AI technology to help communications companies accelerate autonomous network journeys.
• Nokia Corporation. (2026, June 23). Nokia advances autonomous networks portfolio with upgraded agentic AI capabilities.

This Report Answers

• The report provides strategic intelligence on the Agentic Artificial Intelligence in Telecommunications and Network Management Market across the segment categories that drive industrial and enterprise purchasing behavior.
• Segment analysis identifies Network Operations Agents as the leading sub-segment within the AI Agent Function segment, with a 38.0% share in 2026.
• Regional outlook evaluates USA, UK and South Korea while Japan, Germany complete the country growth comparison.
• Competitive analysis profiles NVIDIA Corporation, Microsoft Corporation and Google LLC alongside IBM Corporation and Amazon Web Services, Inc., followed by additional active providers within the category.
• Category assessment covers demand across primary segment groupings within the market, evaluated by value (USD) and share.
• Use-case assessment covers key application areas and end-use sectors identified in the market analysis.

What does the Agentic Artificial Intelligence in Telecommunications and Network Management Market cover?

The Agentic Artificial Intelligence in Telecommunications and Network Management Market covers the systems, services, and software categories defined by AI Agent Function, Network Application, End-use Segment and related market attributes.

The Agentic Artificial Intelligence in Telecommunications and Network Management Market covers the full range of products and services segmented by AI Agent Function, Network Application, End-use Segment, Organization Type, and Deployment Architecture within the 2026-2036 forecast horizon. Coverage includes Network Operations Agents, the largest sub-segment within the AI Agent Function segment, and extends across all primary categories identified in the report.

The market differs from adjacent consumer or industrial categories because commercial value comes from the function and performance requirements captured within the supplied segmentation framework. Commodity components and general-purpose categories remain outside the boundary unless they are explicitly formulated or configured for the defined market application.

What is included in the scope?

Agentic Artificial Intelligence in Telecommunications and Network Management Market products and services deployed across the major segment categories and geographies profiled in the report.

The scope includes all product categories segmented by AI Agent Function, Network Application, End-use Segment, Organization Type, and Deployment Architecture covered through secondary research, supplier validation, and demand modeling. Network Operations Agents, the leading sub-segment within the AI Agent Function segment, is included with full value and share analysis alongside the complete set of profiled countries, companies, and end-use applications identified in the report.

What is excluded from the scope?

Commodity inputs, general-purpose goods, and unrelated service lines are outside the scope.

The scope excludes products and services that are not specifically designed, configured, or deployed for the Agentic Artificial Intelligence in Telecommunications and Network Management Market. General-purpose or horizontal categories that may be used incidentally across multiple markets are excluded unless they are sold within a product or service bundle specific to the market under analysis. Adjacent categories and standalone commodity components remain outside the boundary unless their principal commercial function falls within the supplied segmentation framework.

How was the analysis built?

Forecasts are validated through supplier checks, industry interviews, and demand-side input that tests assumptions on adoption, product trends, pricing, and regional dynamics. Portfolio mapping, regional demand assessments, and distributor feedback help confirm market direction. Ongoing monitoring of regulatory developments and competitive product launches supports continuous model and forecast updates.

• Data Validation and Update Cycle:
  • Forecasting uses activity-level data, product adoption rates, attachment ratios, application demand, technology penetration curves, and average pricing benchmarks. Models also incorporate regulatory impact, regional adoption patterns, technology substitution effects, and format or deployment preferences across end-use applications and geographies.
• Market-Sizing and Forecasting:
  • Desk research draws on company reports, investor presentations, product specifications, press releases, patent filings, and third-party market data. Government publications, regulatory filings, standards documentation, and industry body reports are also reviewed. News monitoring and business intelligence sources are systematically evaluated to track product launches, partnership activity, and competitive positioning.
• Desk Research:
  • Primary research includes interviews with product managers, technology suppliers, system integrators, procurement specialists, and end-user organizations. Input from domain experts, application engineers, and sales teams involved in product specification, deployment, and commercialization is evaluated alongside buyer feedback on purchasing criteria, adoption drivers, and competitive evaluation.
• Primary Research:
  • 120+ sources, 40+ company portfolios, 25+ countries, 20+ interviews.