This 2-page brief presents Agentic Data Quality as an ADAM foundational solution that closes the gap between detecting data quality issues and actually resolving them, since many existing tools flag problems but do not drive timely correction, leading to long issue lifecycles and reduced trust in enterprise data. Brillio proposes a set of agents that automate the workflow end to end: onboarding agents identify datasets needing checks, execution agents recommend data checks dynamically, monitoring agents continuously scan for issues, and corrective action agents perform root-cause analysis and recommend or execute fixes with human approval. An example in financial reporting shows agents diagnosing mismatches across sales, billing, procurement, and expenses, then triggering reprocessing or f

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