On September 17, telecom giant Nokia and Big Tech’s Microsoft expanded global telecom partnership, combining Nokia Data Suite with Microsoft Fabric to advance telecom network automation through AI agents, trusted data, and unified analytics across secure cloud, hybrid, and multi-vendor telecom environments worldwide.
The collaboration targets a major obstacle slowing telecom AI: fragmented network data. Therefore, connecting telecom information with Microsoft’s AI tools could help operators prepare data faster and use AI in daily operations.
Turning Telecom Data Into AI-Ready Networks
The partnership creates a shared data layer for AI network automation. Nokia Data Suite supplies ready-made telecom data products, reducing preparation work for operators.
Microsoft Fabric adds OneLake, analytics, governance, Copilot, Foundry, and Power BI. Together, they form an AI network automation platform connecting network and enterprise information.
The pros of leading AI network automation platforms include faster access to trusted data and less preparation before AI systems can use it.
“Nokia and Microsoft are bringing the right data, at the right time, for the right reason for telecom operators worldwide. Together, we are helping networks evolve from static infrastructures into programmable, AI-native platforms,” said Vivek Jaiswal, senior vice president of Autonomous Networks at Nokia.
The system supports agentic AI network automation across multi-vendor environments. It can run in cloud, hybrid, and on-premises infrastructure while supporting different technical and regulatory needs.
For operators, telecom network automation could become more practical. AI assistants can examine problems, suggest responses, and trigger approved workflows while engineers remain responsible for oversight.
“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 of Worldwide Telco & Media at Microsoft.
AI Agents Move Closer to Daily Network Operations
Initial use cases show how AI network automation could help teams solve problems faster. In autonomous Voice over New Radio assurance, agents identify unusual behavior and recommend actions.
Geo-experience maps radio access network sessions to geographic areas, allowing an AI network automation platform to combine subscriber and radio data when locating coverage or capacity problems.
Predictive maintenance brings telecom network automation into fault prevention. Agents can compare historical and real-time data to identify warning signs before failures affect customers.
That speed is among the pros of leading ai network automation platforms for large operators. Engineers can use AI-generated analysis instead of manually checking several separate systems.
Nokia and Microsoft also present the system as one of the best network automation solutions for telecom service providers needing to combine network and business data under a governed platform.
A telecom network automation tool still requires clear control. Nokia says AI assistants are designed as copilots for engineers, offering recommendations and workflow support rather than removing human supervision.
As the partnership grows, agentic AI network automation could handle more complex tasks across radio networks, service assurance, and fault management. More customer deployments and use cases are planned.
The wider aim of telecom network automation is to make networks faster to manage without giving up human control. AI can handle repetitive analysis while engineers oversee higher-impact decisions.
Nokia also sees AI network automation for enhanced efficiency as a path from reactive maintenance toward earlier; data-led action as 5G networks become larger and more complex.
The solution is present, and both companies plan to expand telecom network automation deployments as operators introduce more AI agents into routine network operations.
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