After publishing research into the use of artificial intelligence (AI) in network automation, which found that the comms industry is rapidly moving to build infrastructure capable of enabling powerful and successful AI, Nokia has unveiled agentic AI capabilities for its fixed network product lines to help drive productivity and operational intelligence across broadband networks.
The global comms tech provider said that with the telecoms industry set to invest $6.2bn in agentic AI by 2030, agentic AI systems capable of autonomous reasoning and decision-making will be a key driver of the cognitive broadband era, enabling networks to move beyond basic connectivity towards self-optimising, AI-driven infrastructures.
Designed for the cognitive broadband era, Nokia’s AI-enabled fixed networks portfolio is claimed to boost user experience, increase operational efficiency and accelerate fibre roll-out. The move will see the supplier embed AI agents and natural language interaction across its Altiplano, Corteca and Broadband Easy platforms, enabling network providers to modernise operations and reduce costs.
Drawing on insights, experience and expertise from over 600 million broadband lines, Nokia said it was confident that the agentic AI capabilities would help operators tackle fibre and Wi-Fi challenges, from design and planning to roll-out and operations. Moreover, it assured that an open and secure AI agent approach would allow providers to integrate their own AI tools and data sources.
How AI agents will benefit network operators
As a result, Nokia said operators would be able to resolve problems proactively, scale operations without adding headcount and diagnose network issues using automated root cause analysis.
Importantly, the tech firm said the AI agents would make an immediate and tangible difference for operators, including lifting first-contact helpdesk resolution rates above 50%, network incident qualification within five minutes, and a 50% reduction in return visits to construction sites and connected homes.
Underpinning this is an open and secure approach that is attributed with integrating AI agents, live data and external services while ensuring compliance, data sovereignty and supplier independence. Operators are said to be able to retain full control and choose to work with a large language model (LLM) that best fits the specific use case, use their own interfaces, or connect data sources as they scale AI across their business.
Specific capabilities attributed to the agents include an AI assistant with a conversational interface that gives technicians and support teams instant access to product knowledge, accelerating training and day-to-day problem-solving.
AI-powered text, voice and image guidance assists field technicians during surveys and installations, and computer vision technology helps validate the quality of work done and build a live digital twin of a fibre-to-the-home (FTTH) network.
In addition, automated diagnostics will be used to detect degradations and prevent outages, giving frontline support teams more operational precision and analytical depth. A troubleshooting agent is designed to improve root cause analysis and speed up remediation across home and access networks, using advanced reasoning to pinpoint faults faster, reduce ticket volume and increase first-call resolution rates.
AI support for field teams and troubleshooting
Commenting on the launch, Nokia’s fixed networks president, Sandy Motley, noted that AI makes users less likely to churn, engineering and helpdesk teams more productive, and field teams able to make more connections more quickly.
“We’re fundamentally changing how home and broadband networks are deployed and run,” she remarked. “AI only works with quality data, and when data is AI-ready. Our recent market outlook on AI in network automation underscored that the industry is rapidly moving to build infrastructure capable of enabling powerful, successful AI.”
Grant Lenahan, partner and principal analyst at Appledore Research, said suppliers such as Nokia, which combine deep domain expertise with real-world scale, were best positioned to deliver reliable outcomes.
“Nokia’s approach reflects many of the right architectural principles, including autonomous control loops, structured data models and open APIs [application programming interfaces], which are critical to making automation easy and AI responses accurate,” he said.
