Nokia and AWS Introduce First Agentic AI-Powered 5G Network Slicing with du and Orange at MWC 2026

Nokia and Amazon Web Services (AWS) have announced a collaboration to deploy the first agentic AI-driven 5G-Advanced network slicing solution in the live networks of du and Orange, presented at Mobile World Congress 2026 (Nokia Press Release, 2026). The breakthrough aims to make 5G networks more intelligent, flexible, and responsive to real-world events.

From Static Slices to Intelligent Networks

Network slicing traditionally divides a 5G network into multiple virtual segments, each designed for a particular application, such as industrial IoT, streaming, or enterprise communications (Nokia Press Release, 2026). Previously, these slices were manually configured and required operator intervention, which made them slow to react to sudden surges in demand, like large concerts, sports events, or emergencies (Rao, AWS, 2026).

According to Pallavi Mahajan, Chief Technology and AI Officer at Nokia, the new solution uses agentic AI to automatically analyse data from traffic, events, maps, locations, and weather, adjusting the network in real time to deliver optimal service (Mahajan, 2026). She explained, “By combining Nokia’s advanced network slicing capabilities with agentic AI, we are enabling operators to deliver premium, intent-based services that adapt dynamically to real-world conditions.”

How It Works

The technology integrates Nokia 5G AirScale base stations, MantaRay SMO, and AI modules with AWS Amazon Bedrock, which provides the foundation models and computing infrastructure to run AI-driven network operations (Nokia Press Release, 2026). The AI modules operate in multiple modes—including autonomous, on-demand, scheduled, or chatbot-guided—allowing operators to control network slices flexibly and efficiently (Mahajan, 2026).

Amir Rao, Global Director at AWS, added that this approach allows networks to respond intelligently to real-world conditions: “By integrating agentic AI through Amazon Bedrock, operators can now deliver context-aware network slices that react dynamically, turning slicing into a true business enabler” (Rao, 2026).

Practical Applications

1. Enterprise and Industrial Networks – The AI continuously monitors network performance indicators such as latency and bitrate and adjusts slices across campuses, business parks, and city areas. This ensures that critical systems—like factories, hospitals, or IoT infrastructure—remain fully operational even under heavy load (Nokia Press Release, 2026). In the past, manual adjustments caused delays and service interruptions.

2. Emergency and On-Demand Slicing – During crises, AI-powered slices prioritise network access for first responders while maintaining quality for high-demand users, such as gamers and streaming customers (Rao, 2026). Previously, emergency traffic often caused congestion and degraded performance.

3. Large Event Optimisation – The AI anticipates network demand for stadiums, concerts, and conferences, allocating capacity for VIP users, broadcasting teams, payment systems, and operational staff (Nokia Press Release, 2026). Earlier methods relied on pre-planned resource allocation, which often resulted in over- or under-provisioned networks.

Key Technology Features

• Edge Slicing: Moves applications closer to end users to reduce latency and improve cloud performance (Nokia Press Release, 2026).

• Amazon EKS Hybrid Nodes: Enables deployment of AI agents and network workloads across both on-premises and cloud infrastructure with unified Kubernetes management (Nokia Press Release, 2026).

• Agentic AI Modules: Leverage multiple sources of open internet data—including events, timetables, traffic, maps, and weather—to continuously optimise network slices in real time (Mahajan, 2026).

Why This Matters

This innovation represents a transition from static, pre-planned 5G networks to AI-native networks capable of self-managing, predicting, and adapting. For consumers, this means smoother connectivity during major events or emergencies. Enterprises benefit from reliable operation for mission-critical applications, while telecom operators gain the ability to offer premium, differentiated services that automatically respond to customer needs (Rao, 2026; Mahajan, 2026).