AI-driven operating model key to cloud-native, autonomous networks | Computer Weekly

Agentic artificial intelligence (AI) has the potential to fundamentally change how telecom networks are operated, but only if their operators build on the right foundations, introduce cloud-native maturity and establish a clear path to integrate autonomy without sacrificing reliability or control, according to a briefing document from The Next Generation Mobile Networks Alliance (NGMN).

The NGMN organisation comprises an association of mobile operators, suppliers, manufacturers and research institutes. Its stated mission is to ensure that next-generation mobile network infrastructure, service platforms and devices meet operators’ requirements while addressing the demands and expectations of end users.

In its report, Cloud native next chapter – agentic AI-based operating models, it offers guiding principles, architectural guidelines and strategic insights to help mobile network operators to support the adoption of Agentic AI into telecom network operating models.

Moreover, NGMN said that it is providing 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.

NGMN stated that the document maps cloud-native maturity levels to corresponding stages of AI readiness, outlining how AI – including generative AI (GenAI) and its more autonomous form, agentic AI – can be progressively integrated into telecom operating models. This phased approach supports a structured transition from early AI experiments through standardised AI-driven workflows toward fully agentic AI-enabled autonomous network operations.

This framework builds 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), and introduces a structured approach to integrate agentic AI-based capabilities into telecom operations.

The study defines five progressive AI adoption levels and maps them to the CNCF CNMM stages for operators to assess their readiness and required next steps to gradually evolve towards more intelligent and autonomous network operations. For each AI adoption level, there is guidance on what is required across technology, people, skills and organisational culture. It also emphasises “the importance of defining clear transformation targets and measuring business outcomes as operators progress along this journey”.

The publication also highlights how the transition towards AI-driven operating models is not solely a technological shift, stating that 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.

“Agentic AI has the potential to fundamentally change how telecom networks are operated, but only if telecom operators build on the right foundations,” said Laurent Leboucher, chairman of the NGMN Alliance board and Orange Group CTO and EVP Networks. “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.”

Bernard Bureau, NGMN board member and vice-president of wireless technology and services at Telus, added: “Cloud-native adoption provides the essential foundation for integrating advanced AI into telecom operations. 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.”