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Agentic AI will likely become a key enabler in creating a credible pathway towards trusted Level 4* autonomous mobile networks, but achieving this will require significant transformation across architecture, standards, security, operations and governance, according to a new industry publication from the Next Generation Mobile Networks Alliance (NGMN). 

‘Network Automation and Autonomy Phase III: Agentic AI for Autonomous Mobile Networks’ explores the motivation, opportunities, requirements, and ecosystem developments associated with applying Agentic AI for network automation in autonomous mobile networks.  

It provides three key insights: a pragmatic reference framework identifying the core components required for Agentic AI-driven network automation; a look at ecosystem maturity and potential or perceived gaps across standards and open-source activities; and a set of considerations to accelerate safe, interoperable and scalable deployment. 

 The publication highlights that while Agentic AI can act as a foundational catalyst for network automation, the success of commercial-scale adoption will benefit from the readiness of comprehensive and reliable support systems, ecosystem alignment and the mitigation of fragmentation risks rather than individual AI model capabilities or technologies. 

It identifies that operators will need robust mechanisms for governance, trust, policy adherence, observability, explainability, operational safety, determinism, assurance, security and cost control.  

Laurent Leboucher, Chairman of the NGMN Alliance Board and Orange Group CTO and EVP Networks, commented: “Mobile network operators (MNOs) find themselves at a decisive inflection point as the telecoms industry enters a new phase of network automation. AI is no longer restricted to analytics, prediction, and closed-loop optimisation. Indeed, the rapid arrival of Agentic AI has introduced the prospect of autonomous systems able to reason, plan, collaborate and execute actions within and across multiple operational domains.  

“However, the complexity of networks and high expectations surrounding customer experience means general-purpose Agentic AI technologies must be used carefully with the right harness and guardrails to bring humans in the loop when needed. This is a learning process in itself where operators will have to take controlled risks.” 

Guangyi Liu, Chief Expert of China Mobile and NGMN Board Director, said: “Review of standards development organisations (SDOs), industry initiatives and open-source activities demonstrates encouraging momentum across the ecosystem in Agentic AI deployments, but despite this the landscape remains largely complex and unevenly mature.  

“Increased collaboration among MNOs, SDOs, vendors, hyperscalers, and open-source communities is therefore important to achieve confidence in the opportunity of large-scale deployments and provide a more unified end-to-end perspective. That means cross-industry coordination on areas such as telecom-grade interfaces and trust mechanisms, as well as shared testing environments, and evidence-based validation of agent behaviour to ensure solutions remain interoperable, secure and fully aligned with operator requirements.” 

Luke Ibbetson, Head of R&D at Vodafone and NGMN Board Director, added: “Capabilities for trustworthiness, security, explainability, observability, interoperability, governance and appropriate human oversight must be in place for Agentic AI in order to accelerate safe, interoperable, and scalable deployment across the telco ecosystem.  

“If the related requirements are met, Agentic AI can help create a realistic route toward trusted Level 4 autonomy where networks are highly autonomous and enable automated decision making, self-optimisation, self-healing and self-management.” 

‘Network Automation and Autonomy Phase III: Agentic AI for Autonomous Mobile Networks’ also highlights how isolated proof-of-concepts will increasingly shift towards operational deployments of Agentic AI prioritising well-controlled, high-value use cases in the coming years, with agents capable of managing complex workflows across multiple network domains. 

One of the main factors determining the success of this will be increased collaboration across the entire telco ecosystem to help reduce the risk of fragmentation and align on interoperable architectures, interfaces and responsibilities. 

The full publication can be downloaded from here.

Further information and all NGMN publications can be found on the website at ngmn.org. 

 *As defined by TM Forum’s Autonomous Networks Project 

 

 

New operator-driven guidance outlines how mobile network operators can adopt AI-based operating models to enable increasingly autonomous network operations.

The Next Generation Mobile Networks Alliance (NGMN) today published new guidance outlining how mobile network operators (MNOs) can evolve their cloud-native network operations towards Agentic AI-based and increasingly autonomous operating models. The publication “Cloud Native Next Chapter – Agentic AI-based Operating Models” provides a framework for Mobile Network Operators to support the adoption of Agentic AI in telecom network operating models, helping operators navigate the transformation across technology, processes, skills, and organisational culture.

Building on NGMN’s Cloud Native Manifesto and established cloud-native frameworks such as the Cloud Native Computing Foundation’s (CNCF’s) Cloud Native Maturity Model (CNMM), the publication introduces a structured approach to integrate Agentic AI-based capabilities into telecom operations. It defines five progressive AI adoption levels and maps them to the CNCF Cloud Native Maturity Model (CNMM) stages, enabling operators to assess their readiness and required next steps to gradually evolve towards more intelligent and autonomous network operations. For each AI adoption level, the document also provides guidance on what is required across technology, people, skills and organisational culture. It further emphasises the importance of defining clear transformation targets and measuring business outcomes as operators progress along this journey.

Through this publication, NGMN shares guiding principles, architectural guidelines and strategic insights to help operators’ transformation and to navigate different levels of autonomy and AI adoption in cloud-native network environments.

“Agentic AI has the potential to fundamentally change how telecom networks are operated, but only if telecom operators build on the right foundations. AI adoption doesn’t happen in isolation; it depends on cloud-native maturity and a clear path to integrate autonomy without sacrificing reliability or control. That’s exactly what NGMN’s framework delivers: practical guidance to help operators embrace AI-driven operations with confidence,” said Laurent Leboucher, Chairman of the NGMN Alliance Board and Orange Group CTO and EVP Networks.

The publication highlights how cloud-native maturity forms the foundation for AI-driven operations. While early stages focus on controlled experimentation and AI-assisted workflows, more advanced stages enable increasingly autonomous network management through closed-loop automation and intelligent orchestration. By aligning cloud-native maturity with AI readiness, operators can adopt AI technologies in a phased and responsible manner while balancing innovation with operational stability.

“Cloud-native adoption provides the essential foundation for integrating advanced AI into telecom operations,” said Bernard Bureau, NGMN Board Member and VP Wireless Technology & Services at TELUS. “By mapping cloud-native maturity levels to AI adoption stages, NGMN offers operators a practical framework to gradually introduce AI-enabled automation — from early experimentation to increasingly autonomous network operations.”

The publication also emphasises that the transition towards AI-driven operating models is not solely a technological shift. Successful adoption requires organisational transformation across people, processes and culture, including new skillsets, responsible AI governance and redesigned operational workflows. AI-enabled tools can support tasks such as network troubleshooting, capacity planning, and predictive operations, enabling more efficient and resilient network management.

“As Agentic AI-based technologies evolve rapidly, NGMN provides operators practical guidance on how to lever them on the transition to Agentic AI-based network operations, in a responsible and scalable way,” said Anita Döhler, CEO of the NGMN Alliance. “By outlining 5 specific stages, this publication provides a roadmap for mobile network operators to evolve their cloud-native platforms towards Agentic AI-enabled operating models, whilst setting clear objectives and measuring business outcomes.”

The full publication “Cloud Native Next Chapter – Agentic AI-based Operating Models” is available for download here.

Collaboration is key to driving the industry’s most important topics such as NGMN’s strategic pillars: Mastering the Route to Disaggregation, Green Future Networks, and 6G. NGMN therefore invites all parties across the entire value chain to join the Alliance in this important endeavour.

During an interview with TelecomTV, Laurent Leboucher, Chairman of the NGMN Alliance Board, Orange Group CTO and EVP Networks, spoke about the importance of NGMN Alliance’s work.

Laurent detailed the main themes of NGMN’s Press and Industry Briefing at #MWC26, including frameworks for network simplification, guidance on cloud-native and AI-based operating models and the Alliance’s recommendations for sustainable networks.

The impact of AI on network traffic and 6G standardisation was also discussed, as well as why flexibility and interoperability would be crucial in the years ahead.