Nokia Adds New Agentic-AI Capabilities Across its Autonomous Networks Portfolio
The latest Agentic AI enhancements enable CSPs to more easily detect security threats, accelerate new service creation, and improve the management of their networks.
Nokia has announced new Agentic AI capabilities within its autonomous networks portfolio that will help Communication Service Providers (CSPs) better automate, secure, and monetize their networks.
Extending the AI capabilities already embedded in Nokia’s autonomous networks portfolio, the latest Agentic AI enhancements enable CSPs to more easily detect security threats, accelerate new service creation, and improve the management of their networks.
These advancements build on Nokia’s existing AI tools to allow CSPs to better detect security threats, accelerate service creation, and improve network management.
Key features include the use of telecom-trained large language models (LLMs) for proactive threat detection and AI agents to streamline tasks like service cataloging and troubleshooting failed orders. Nokia Bell Labs’ AI models also contribute by enabling advanced anomaly detection and network fault prediction.
Industry analysts recognize Nokia as a leader in areas like cybersecurity and network automation, and these updates are seen as a step toward fully autonomous networks that can sense, think, and act independently, strengthening Nokia’s position in the telecom sector.
“CSPs around the world are actively pursuing higher levels of network autonomy to achieve increased operational efficiency and offer their customers personalized experiences.
AI is the catalyst to unlock L4/L5 autonomy, manage complexity, and orchestrate actions across network domains and operational functions,” said Kal De, SVP Product and Engineering, Cloud and Network Services at Nokia.
Agentic Ai for Telco Operations
Writing for Telecoms.com, Jitin Bhandari explains the new trend of ‘Agentic AI’ and what this means for Telcos.
He says these autonomous, persona-based agents are best thought of as intelligent entities designed to augment human efforts, streamline operations and tackle the complexities of modern networks.
In a companion article Marcelo Cheminn Madruga defines an implementation framework and roadmap for Telcos to implement this vision for Agentic Ai.
In this keynote presentation, Wim Henderickx explores the essential requirements for a successful path toward network automation. He delves into the significance of making automation consumable, predictable, trustable, and intelligent. As an example, he illustrates how the Nephio open-source project addresses these needs in the context of 5G, and he emphasizes the role of Kubernetes in driving the adoption of network automation.
Telecomms LLMs
Nokia’s telecom-trained Large Language Models (LLMs) are specialized AI systems integrated into its autonomous networks portfolio, designed to enhance automation, security, and operational efficiency for Communication Service Providers (CSPs).
Developed with contributions from Nokia Bell Labs, they are tailored to the telecommunications domain through training on telecom-specific datasets, enabling them to address complex network management tasks with a deep understanding of the industry’s unique language and challenges.
Nokia’s LLMs stand out due to its telecom heritage and Bell Labs’ AI research prowess. Unlike general-purpose LLMs, they’re purpose-built for CSPs, offering a competitive advantage in areas like cybersecurity (where Nokia is a recognized leader) and network automation. They align with Nokia’s strategy to push toward Level 5 autonomy—fully self-managing networks—positioning the company as a frontrunner in the telecom AI race.
In short, Nokia’s LLMs are telecom-savvy AI powerhouses, driving smarter, more secure, and more autonomous networks by blending language understanding with deep industry expertise.
