
Enterprises can use AI to help correlate information and automate operations, but it doesn’t eliminate the need to address underlying operational problems. “AI can overcome data fragmentation across tools, but it’s not going to overcome bad data and bad operations in general,” McGillicuddy said.
AI takes on more of the workload
Enterprises are now applying AI to that operational data. Thirty-two percent of respondents said they use AI extensively across observability tools, 51% use it in selected areas, and 13% are still piloting it. Use cases shared with EMA included incident summaries and explanations, alert correlation and noise reduction, capacity forecasting, anomaly detection, predictive analytics, and root-cause analytics.
Organizations that reported extensively using AI also said they had greater confidence in their observability unification strategies. Fragmented or inconsistent data can limit AI effectiveness, and organizations also cited concerns about inaccurate outputs and security and compliance risks.



















