Nokia and Microsoft Build Agentic Data Platform for Telecom AI

Nokia and Microsoft Accelerate Network Automation with Agentic AI Platform

Nokia and Microsoft announced an expansion of their partnership on September 17, 2026, focused on building an agentic, unified data foundation designed to speed AI-driven network automation for telecommunications providers. The collaboration integrates Nokia Data Suite's pre-built telco data products with Microsoft Fabric's unified analytics and governance capabilities, according to details first reported by Nokia.

The platform enables operators to access high-quality, trusted network data in minutes rather than the weeks typically required through traditional data integration methods. This acceleration addresses a fundamental barrier to AI adoption in telecom: the time-consuming process of preparing and operationalizing complex network data.

Why it matters

Telecom operators have struggled to move AI from pilot projects to production-scale network operations, largely because fragmented data environments make it difficult to build reliable autonomous systems. By combining pre-built, semantically modeled telco data with enterprise-grade analytics infrastructure, this partnership creates a faster path to operational AI that can handle multi-vendor, cross-domain network environments — a critical requirement for real-world deployments.

From Data Integration to Autonomous Operations

Nokia Data Suite provides reusable telco data products with what the company calls "glass-box" data quality controls and telco-specific semantic modeling. These features are designed to ensure transparency and explainability in AI-driven network decisions. Microsoft Fabric contributes unified data storage through OneLake, along with analytics tools and AI-native applications including Microsoft 365 Copilot, Foundry, and Power BI.

The integrated solution allows operators to provision Nokia's data products on demand and combine them with Microsoft Fabric's enterprise, IT, and third-party data sources. This architecture supports hybrid and cloud infrastructures, including on-premises deployments, giving operators flexibility to meet regulatory requirements while advancing automation strategies.

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

Initial Use Cases Deploy Autonomous Agents

The platform is available now with several go-to-market use cases that demonstrate agentic AI capabilities. For autonomous VoNR (voice over new radio) assurance, agents identify service anomalies, conduct root cause analyses, and recommend remediation actions with comprehensive observability across network, service, and subscriber dimensions.

A geo-experience capability uses AI and machine learning to map radio access network subscriber sessions to precise geographic locations, identify users experiencing degraded performance, and pinpoint coverage or capacity issues. Agents analyze correlations between subscriber, network, and RF data to provide actionable recommendations for both network-sliced and standard 4G/5G users.

Predictive maintenance and fault management represents a third initial use case, where agents analyze historical and real-time data to anticipate network issues before customer impact occurs.

Throughout these applications, AI-driven operational assistants function as copilots for network engineers, providing contextual insights, recommended actions, and automated workflow execution. Silvia Candiani, Corporate Vice President of Worldwide Telco & Media at Microsoft, noted that telecom providers are ready to move AI into everyday operations but require trusted data, strong governance, and scalable platforms to do so.

The collaboration builds on existing Nokia and Microsoft partnership activities spanning cloud, data, AI, and cybersecurity, with ongoing expansion of autonomous network use cases and customer deployments planned. Details were first reported by Nokia.