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Itential Discusses AI in Networking and the Importance of MCP

Source Decision Insights Coverage Published November 17, 2025 Companies 1
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76th article in the last 90 days, one of 114 articles referencing Itential. Previous coverage: Corning’s network refresh and AI strategies highlighted in Itential Insights (Nov 2025).

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Best suited for

Persona
Platform / Infrastructure Operations Leader
Decision stage
How to start
Adoption curve
Early Adopters

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The blog discusses the intersection of Artificial Intelligence (AI) and network automation, emphasizing the need for clear frameworks over buzzwords. This insight is particularly relevant for IT leaders considering the adoption of AI technologies in their networks.

Product Update

The post focuses on the Model Context Protocol (MCP), which enables AI to interact with systems while maintaining control and safety. MCP serves as a bridge between reasoning systems and traditional infrastructure.

The author critiques the common misunderstanding of MCP, where organizations treat it as a simple wrapper for existing APIs. Instead, the true potential lie in defining clear actions that AI can execute, ensuring safety and operational integrity.

Technology Strategy

The effectiveness of AI in network operations relies heavily on structuring tasks in a controlled manner. The author suggests focusing on specific outcomes and developing small, actionable commands for AI to follow.

The goal is to allow AI to operate within predefined boundaries while ensuring oversight and traceability of actions taken, maintaining trust in automated systems.

Security & Compliance

As organizations incorporate AI technologies, they must prioritize security frameworks. Implementing AI without proper guardrails could lead to increased vulnerabilities within network operations.

Establishing a framework that dictates what AI is allowed to access, along with approval processes for actions, is essential to maintain security while leveraging AI capabilities.

Customer Use Case

The blog highlights practical applications of AI, particularly in operations rather than configuration. Tasks such as drift detection and compliance checks are identified as areas where AI can effectively assist teams.

However, the author cautions against allowing AI to make critical changes autonomously, suggesting that it should only facilitate decision-making for change initiatives.

Conclusion

In summary, while AI will not fully automate network management in the immediate future, it can enhance efficiency and trust in operations. The adoption of MCP, with a focus on well-defined use cases, is presented as a path forward for integrating AI responsibly in network environments. This summary reflects key insights from the original post, emphasizing the importance of clarity and intention in AI deployment.

Blog post, originally published at itential.com.

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