Log management for AI workloads: How to bring your logs and telemetry plan into the AI-first century

AI workloads are overwhelming traditional log management systems, exposing limits in how teams capture, store, and correlate telemetry. A five-point action plan covers: unifying all telemetry signals on a single platform, correlating logs with traces for causation, controlling costs by eliminating rigid schemas and rehydration overhead, standardizing instrumentation at ingest, and enabling preventive operations through real-time contextual analytics. Key stats from a 2026 survey of 450 IT leaders highlight that 85% of organizations struggle to ingest logs at AI scale, 74% cite indexing and rehydration costs as barriers, and 84% say customer trust in AI depends on predictive log analytics.