A Fortune 100 company recently faced a critical issue with its customer churn prediction model failing just before launch, due to a broken ingestion pipeline that went undetected. The problem was not with the AI model or strategy, but rather with brittle and reactive data plumbing. This highlights the challenges of traditional observability tools that provide visibility but leave teams drowning in dashboards and manually triaging alerts. To address this, Acceldata is rearchitecting its system to introduce autonomous intelligence into the data layer through Agentic Data Management (ADM). ADM brings cognition into data operations by introducing intelligent agents that detect, reason, and resolve issues without human intervention, resulting in a living, adaptive system that is always on and aligned with business needs. This paradigm shift aims to eliminate decision latency, data downtime, and broken trust across business units, while providing real autonomy across the entire data estate through automation of workflows, elimination of bottlenecks, and enforcement of quality and lineage.