Texas agencies are swimming in data yet struggle to unlock its value because privacy statutes, fragmented governance processes, and uneven data quality make modernization risky and slow.  This session shows how state entities can treat data itself as the control plane - building stewardship, lineage, and quality checks directly into every AI and automation initiative - so transformation accelerates without sacrificing compliance.

Join us while we unpack the “AI Factory: Data First Edition” blueprint, a framework that:
•  keeps PII in-place and enforces controls through fine-grained tagging and policy-as-code.
•  automatically registers new sources, tracks lineage, and launches quality scores before any model is trained.
•  embeds continuous profiling so agencies spot drift, bias, or missing values early - cutting analytic rework 30-40 %.
•  accelerates licensing, benefits, and permitting workflows by linking clean, governed data to GenAI assistants.

We will illustrate the approach with three Texas-specific stories, including an in-progress PoC inside the ATOS-hosted “AI Factory” sandbox that demonstrates multi-agency, multi-tenancy data governance; plus, pilots for records classification and fraud analytics.