Nokia and Microsoft Built a Data Foundation for AI Network Agents

"Telecom providers are ready to move AI from experimentation into everyday network operations."
On September 17, Nokia and Microsoft announced a data platform designed to solve the problem of getting network data from multiple domains and vendors into a form that AI agents can reliably use, a process that can take weeks using traditional integration methods.
The platform combines Nokia Data Suite's prebuilt telco data products with Microsoft Fabric's unified analytics and AI infrastructure, according to the companies.
Nokia Data Suite provides what Nokia describes as glass-box data quality controls, making the data used by AI systems transparent and explainable rather than opaque, alongside telco-specific semantic modeling that allows individual data products to be provisioned on demand and reused across different applications.
Microsoft Fabric contributes OneLake storage, Power BI, Microsoft Foundry, and Microsoft 365 Copilot. The combination is intended to give AI agents access to trusted, unified data in minutes rather than weeks, addressing what Nokia and Microsoft describe as a foundational bottleneck in moving telecom AI from experimentation to production.
"Telecom providers are ready to move AI from experimentation into everyday network operations, but that requires trusted data, strong governance and platforms that can scale," said Silvia Candiani, Corporate Vice President, Worldwide Telco and Media at Microsoft.
The three initial use cases named at launch include Autonomous VoNR assurance which deploys AI agents to identify voice-over-new-radio service anomalies, run root cause analysis, and recommend remedial actions using combined network, service, and subscriber observability, a 360-degree view that traditional siloed monitoring tools cannot provide.
Geo-experience correlates subscriber, network, and radio-frequency data to pinpoint which users are experiencing degraded RAN performance and identify the specific coverage or capacity hotspots causing it, enabling targeted interventions rather than broad network adjustments.
Predictive maintenance uses agents to analyze historical and real-time network data to surface potential issues before they reach customers, according to the companies.
AI assistants operate as copilots for network engineers, providing contextual insights, recommended actions, and automated workflow execution, within clearly defined governance boundaries.
Human oversight is preserved by design rather than treated as a compliance afterthought. The solution supports multi-vendor, cross-domain environments and hybrid, cloud, and on-premises deployments, allowing operators to meet regulatory requirements while advancing AI 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, Autonomous Networks at Nokia. "Together, we are helping networks evolve from static infrastructures into programmable, AI-native platforms."
The announcement extends an existing Nokia-Microsoft partnership spanning cloud, data, AI, and cybersecurity. It arrives one day after Nokia disclosed eight new AI-RAN operator trials across North America, Europe, Asia-Pacific, and the Middle East, connecting the data layer announcement directly to the radio access network deployment momentum disclosed simultaneously.
Key Takeaways
- Nokia and Microsoft launched a data platform to enhance AI integration in telecom networks.
- The platform speeds up data access for AI agents from weeks to minutes.
- Nokia's Data Suite ensures data transparency and quality for AI applications.
- Microsoft Fabric provides unified analytics and storage solutions for telecom data.
- The collaboration aims to transition AI from experimentation to daily network operations.