Operations | Monitoring | ITSM | DevOps | Cloud

Datadog has been named a Leader in The Forrester Wave: AIOps Platforms, Q4 2026. We believe this placement reflects Datadog’s commitment to transforming observability into autonomous operations with a single integrated platform where AI agents detect, investigate, and remediate production issues, while engineers stay in control. Close dialog.

A critical application slows overnight. Monitoring identifies an unhealthy component, and an engineer finds a familiar remedy: restart a service. The command takes seconds. Determining whether the restart will restore the application or disrupt another dependency takes far longer. That is the real challenge in enterprise incident remediation. Most IT teams already know how to automate a task.

For enterprise IT leaders, the question is no longer whether AI agents can help run IT operations, but how to scale them beyond pilots and into the everyday work of keeping the business online. It’s no coincidence that this year’s Gartner IT Infrastructure, Operations & Cloud Strategies Conference (IOCS) opens with a keynote dedicated to scaling agentic AI to enable autonomous IT operations. At BigPanda, we’ve seen a shift from the ITOps leaders we work with every day.

When something breaks on a large network, the alerts arrive from every direction. Routers, firewalls, cloud gateways, and applications each report their own symptoms. The evidence that explains the incident is scattered across anomalies, configuration changes, topology, and past incidents, and an engineer has to piece it together by hand. Loom is the correlation and root cause agent in Selector Foundry, the agentic NetOps platform built on Selector’s existing AIOps and Observability platform.

The debate is no longer whether AI belongs in ITOps; it’s about how quickly it can be implemented, how to measure it, and who’s accountable when it acts. And although IT leaders across industries are scrambling to integrate agentic AI into their operations, those deployments are facing serious challenges. A new Harris Poll survey of more than 300 U.S. data and AI decision-makers puts a number on the problem.