Nokia, AWS demo agentic AI network slicing with Du, Orange

The use of artificial intelligence (AI) in networking is increasing rapidly, with the latest stage in this technological evolution seeing comms tech firm Nokia announce a collaboration with Amazon Web Services (AWS) to bring the first agentic AI-powered 5G-Advanced network slicing solution in a live 5G network.

The intent-based 5G slicing innovation combines Nokia’s network slicing with AWS AI platform technologies to empower comms providers in delivering premium services precisely where and when they are needed.

Outlining the challenge that they believe is facing the industry, Nokia and AWS said that providers can face challenges optimising network performance during unpredictable events such as traffic surges, emergencies or mass gatherings, which can result in suboptimal service quality and inefficient resource utilisation.

Hosted by AWS, the autonomous network slicing intelligence dynamically adapts and manages even the most challenging traffic conditions across varied geographical areas. The agentic AI-powered approach is said to be the key to unlocking “significant” customer value across diverse applications and use cases by creating premium services that respond intelligently to dynamic conditions, ensuring optimal performance precisely where and when customers need it. 

The end-to-end advanced network slicing technology across RAN-transport-core especially utilises Nokia’s 5G AirScale base station, MantaRay SMO and agentic AI modules, which are seamlessly integrated with the Amazon Bedrock artificial intelligence platform.

The agentic AI modules operate in multiple modes: chatbot, on-demand, scheduled and autonomous. All modules interact with Amazon Bedrock via APIs. Furthermore, applications and use cases powered by agentic AIs are enhanced with Nokia’s Edge Slicing solution, bringing cloud applications and workloads directly to mobile users and devices over high-capacity, secure and low-latency networks.

Nokia noted that its AI slicing technology uses agentic AI to analyse real-world internet data, including locations, events, traffic, incidents and maps to deliver adaptive network slicing. Cited typical use cases for the agentic AI-powered 5G-Advanced network slicing include intent-based enterprise and industrial slicing, on-demand slicing with agentic AI, and agentic AI for mass events.

As regards to the former, the intent-based enterprise and industrial slicing technology will see use in measuring live network KPIs such as bit rate and latency, and autonomously adjusts RAN policies to meet enterprise SLAs across campuses, business parks and city areas. This is intended to enhance premium slicing services for critical applications in manufacturing, the internet of things (IoT), drones, smart cities, hospitals, energy transportation and ports.

On-demand slicing with agentic AI also boosts network performance for selected 5G base stations. When activated by external data, Nokia believes that this service will provide first responders and public safety authorities with better network connectivity during emergencies. On-demand network slicing with agentic-AI is said to preserve quality of service for premium 5G+/5G Advanced and FWA customers using gaming, streaming, XR and AI applications in response to major traffic surges, weather conditions and environmental changes.

Nokia added that agentic AI for mass events will deliver much broader capacity availability during high-demand moments such as concerts and sporting events. AI analyses network data, infers patterns and sets slicing policies for scheduled events, optimising premium 5G slicing for VIP spectators, payment applications, fan engagement, video broadcasting and operational crews in arenas, parks and conference centres.

Operators Du and Orange are the first to explore the innovation in their respective networks. In November 2024, Nokia and United Arab Emirates (UAE) telecoms and digital services provider du carried out a transport network slicing trial to gain benefits of dedicated infrastructure and reduce overall energy consumption.