en.Wedoany.com Reported - Nokia has integrated agentic artificial intelligence technology into its Network Services Platform (NSP), enabling network operators to deploy AI agents that can reason and take actions within real network contexts.
As AI traffic grows, the scale and complexity of IP networks continue to increase, putting pressure on operators to improve efficiency and reliability while maintaining operational control. Nokia notes that many operators remain cautious about applying AI in network operations due to concerns over explainability, trust, and risk. By embedding agentic AI directly into a platform that already serves as the authoritative controller for IP networks, Nokia positions its NSP solution to address these concerns.
The NSP builds AI agents on an accurate and continuously updated network view that includes topology, protocol behavior, configuration status, service relationships, and recent network changes. This enables AI agents to reason based on network facts rather than inferences or fragmented data, and to operate within operator-defined intents, policies, and access controls. Additionally, the solution supports communication with external agents across the operator's multi-vendor, multi-domain network via AI protocols such as the Model-context protocol (MCP).
Nokia illustrates the practical significance of this initiative with a troubleshooting use case. The AI-driven troubleshooting agent is the first use case built on this framework, designed to help operators locate root causes faster, reduce operational noise, and resolve IP network issues.
Sasa Nijemcevic, Vice President and General Manager of IP Network Automation Software at Nokia, stated that the industry is rapidly moving toward AI-native operations, but trust remains a decisive factor. Nokia enhances the NSP with AI agents based on an agentic framework in a way that respects actual network operations. This will profoundly impact how operators manage networks, enabling them to significantly improve operational capabilities and accelerate the journey toward autonomous networks, starting with high-impact use cases like troubleshooting—a gradual, pragmatic step toward AI-native networks.
Grant Lenahan, Partner and Principal Analyst at Appledore Research, commented that efficient and accurate AI reasoning relies on high-quality data and ontological relationships, not specific AI models. Nokia's NSP builds a broad AI-native infrastructure on trusted data and operational norms, providing a solid, secure foundation for numerous AI use cases. Domain expertise is the most critical quality factor when designing effective automation for complex networks.
Nokia stated that for operators, this move provides a flexible foundation that allows multiple AI use cases to be introduced over time without creating isolated solutions. For end users, it will deliver faster issue resolution and higher service reliability, reducing the likelihood of prolonged or cascading outages. The new AI capabilities for the NSP will be commercially available by the end of this year.
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