7 lessons for IT leaders on using observability to monitor AI applications

To avoid "measurement debt," IT leaders must integrate observability into AI application MVPs to provide verifiable proof of ROI from the outset. Effective strategies include using standardized telemetry, monitoring quality-based signals rather than just uptime, and leveraging provider-supplied data for accurate cost tracking. Furthermore, leaders should avoid high-cardinality tagging to prevent observability expenses from spiraling alongside application usage.