Nokia and Microsoft Deploy AI Agents for Telecom Network Automation

Integration eliminates weeks-long data preparation

Nokia and Microsoft have expanded their partnership to deliver agentic AI automation for telecom network operations, according to Telecom Tech News. The integration connects Nokia Data Suite directly with Microsoft Fabric, allowing carriers to deploy automated network management across their infrastructure in minutes rather than the weeks typically required for manual data ingestion projects.

The architecture links Nokia's modular data products into Microsoft Fabric's OneLake storage environment. Nokia packages network telemetry feeds with data quality verification and telecom-specific semantic modeling, creating transparent inputs for machine reasoning. Carriers can then integrate these pipelines with enterprise IT systems and third-party data sources on demand.

"Nokia and Microsoft are bringing the right data, at the right time, for the right reason to telecom operators worldwide," said Vivek Jaiswal, SVP of Autonomous Networks at Nokia. "Together, we are helping networks evolve from static infrastructures into programmable, AI-native platforms."

Why it matters

Telecom operators have struggled to move AI from pilot projects into production due to data preparation bottlenecks and integration complexity. This partnership addresses that barrier by providing query-ready network data that works immediately with Microsoft's analytics tools, including Power BI and Microsoft 365 Copilot. The result is a practical path for carriers to implement autonomous network operations while maintaining data sovereignty and governance requirements.

Real-time remediation across live networks

Autonomous agents execute real-time fixes across multiple deployment scenarios. In voice over new radio (VoNR) networks, automated agents maintain continuous observability across service layers, physical nodes, and subscriber sessions. These systems detect operational anomalies, trace root causes, and dispatch remedial commands without human intervention.

For radio access network diagnostics, the platform's Geo-experience engine correlates subscriber sessions with radio frequency measurements and geographic coordinates. Network teams can isolate degraded mobile performance and identify cell coverage deficits. The software evaluates performance trends for 4G and 5G connections alongside dedicated network slices, then generates specific remedial actions for field engineers.

Predictive maintenance agents analyze historical and live operational data simultaneously to resolve hardware faults before service degradation occurs. Throughout these operations, AI assistants function as copilots for engineering personnel, handling repetitive cross-domain tasks while enforcing policy constraints and requiring manual approvals for critical actions.

Deployment flexibility for data sovereignty

The joint solution operates across hybrid topology, private cloud, and on-premises environments, enabling regional operating units to comply with strict data sovereignty regulations. Silvia Candiani, Corporate VP of Worldwide Telco & Media at Microsoft, noted that telecom providers need "trusted data, strong governance, and platforms that can scale" to move AI into everyday network operations.

The solution is immediately available for commercial deployment, allowing operators to shift human-in-the-loop workflows into live production environments.

These details were first reported by Telecom Tech News.