How AI workloads are changing what logs must deliver, forcing a new strategy

As AI workloads drive a massive surge in telemetry volume, traditional log management is becoming prohibitively expensive and operationally risky due to fragmented tools and data-discarding cost-cutting measures. To build trust in autonomous systems, organizations must transition toward unified observability, integrating logs with traces and metrics into a single, high-fidelity context for more efficient and accurate analysis.