Data Quality in the Agentic AI Era

As AI utility increases, organizations are rethinking how they monitor and maintain data quality at scale to deliver trusted data for confident decisions. But traditional approaches often fall short—failing to keep up with chaos of data sprawl, silos, and ever-growing business demand.

Enter agentic AI.

Agentic AI shifts the paradigm from manual data quality rule creation to intelligent automation. Alation’s Data Quality Agent uses metadata, usage patterns, and generative AI to recommend and run the right data quality checks—at scale and with minimal effort. More importantly, it helps close the data trust gap—the divide between data producers and consumers—by surfacing and fixing the issues that matter most.

Download this whitepaper to discover:

• Why today’s data quality challenges demand more than GenAI and ML

• How agentic AI helps teams pinpoint critical data to monitor

• Use cases from global enterprises tackling alert fatigue, scaling issues, and trust gaps

• How Alation Data Quality accelerates remediation and builds trust—without adding complexity

Whether you’re starting from scratch or scaling an existing data quality program, this guide offers a smarter, faster path to clean, trusted data.