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The latest News and Information on AIOps, alerting in complex systems and related technologies.

From Tools to Teammates: A Practical Framework for AI Agents in Network Operations - Du'An Lightfoot

AI agents are quickly moving from experimentation to real-world deployment in network operations — but how do you adopt them without introducing unnecessary risk? In this session from AI for Network Leaders – Powered by Selector, Du’An Lightfoot shares a practical framework for building and deploying AI agents in production network environments. He covers: This session cuts through the hype and provides a clear, actionable model for teams looking to move from AI as a tool to AI as a teammate.

AI Meeting Bots Were Just the Beginning. Meet the AI Collaborator

Why the next era of enterprise AI isn’t about note-taking — it’s about digital workers who actually show up and do the work. There’s a moment every IT operations leader knows well. A critical incident hits at 2 PM on a Tuesday. Within minutes, a war room meeting spins up — a Google Meet or Teams call crowded with network engineers, SRE leads, cloud architects, and storage admins, all staring at dashboards and talking over each other. Someone is manually pulling syslog data.

Modern IT and the Burden of Accountability

The leaders responsible for modern IT environments rarely talk about features first. They talk about responsibility. In conversations at Nexus Live 2025, ScienceLogic’s annual customer conference, executives and architects across healthcare, federal systems, managed services, telecom, and enterprise IT described modernization not as a tooling upgrade, but as an escalation of accountability.

The Shift Toward Autonomous Enterprises

In our previous post, Navigating the Complexities of Scaling AI in Enterprise Operations, we explored the “cost–human conundrum”, balancing the promise of automation and the realities of economics, skills, and governance. That discussion highlighted a critical inflection point: scaling AI is not just a technical challenge, but an organizational one.

The Trust Layer: Why Enterprise AI Needs a Gateway Before It Needs More Models

Enterprise AI does not have a model problem. It has a trust problem. Before organizations invest in larger models or additional agents, they need a control layer that governs how those agents operate inside production systems. Without that layer, autonomy does not scale. If you talk to any enterprise leader right now, you’ll hear the same question.