TRAIGA Compliance: The Complete Guide to the Texas Responsible AI Governance Act

TRAIGA does not require private deployers to maintain an AI system inventory. We recommend one anyway: a structured register that documents each system's purpose, the decisions it informs, the data it processes, the vendor (if third-party), and the human oversight in place.

An inventory is the foundation of a defensible governance record. Because TRAIGA liability is intent-based, the practical way to show your AI is not being used for a prohibited purpose is documentation — and an inventory is where that record begins.

An AI inventory is most useful when it stays current. As you deploy new AI tools — especially in fast-moving clinical, HR, and operational contexts — keeping the register updated helps you respond quickly if the Texas Attorney General ever asks questions.

TRAIGA does not mandate a documented risk assessment for private deployers, but a structured review is one of the strongest ways to build a defensible record. It evaluates the potential harms a system could cause, the affected population, and the oversight that mitigates those risks.

A structured assessment also supports TRAIGA's safe harbors. Substantial compliance with the NIST AI RMF, internal and adversarial (red-team) testing, and following applicable state-agency guidelines are recognized defenses — and each is far easier to demonstrate when your reviews are documented rather than informal.

We recommend repeating reviews on a defined schedule and whenever you make material changes to a system, its data inputs, its use case, or its deployment context. A living assessment is more persuasive evidence of good-faith governance than a one-time snapshot.

Building on the risk review, we recommend implementing governance controls proportionate to the risks you identify. For higher-risk AI — particularly systems used in healthcare, employment, credit, or housing — controls typically include human oversight, data governance procedures, and defined escalation paths.

Documenting controls, assigning them to responsible parties, and tracking completion gives you evidence that governance is actually operating — not just intended. That evidence is what helps rebut an allegation of prohibited intent under TRAIGA.

Controls are not static. As AI systems evolve and new risks emerge, updating the control set keeps your governance record current and credible. None of this is a TRAIGA mandate for private deployers — it is best practice that strengthens your position.

Enacted TRAIGA does not impose a general public-disclosure duty on private deployers. The statute’s affirmative disclosure obligations fall mainly on government entities, plus a narrower duty for healthcare providers to disclose AI use in treatment and healthcare-service contexts.

If you are a government entity or a healthcare provider, generating clear, plain-language notices is a real obligation — not technical documentation, but accessible notice that AI is being used. Texas SB 1188 (effective September 1, 2025) adds related healthcare requirements around AI-generated records and patient notification.

For private deployers outside those contexts, maintaining consistent disclosure records is a best practice that supports transparency and a defensible governance posture, even though it is not statutorily required.

TRAIGA does not require private deployers to report AI incidents to a regulator within a set timeframe — there is no statutory incident-reporting regime for private companies. We still recommend maintaining a structured internal log of incidents where a system caused or risked unintended harm, produced a discriminatory outcome, failed materially, or was used outside its approved scope.

A good internal log captures the affected system, the nature of the incident, a severity assessment, the investigation, and the remediation taken. Keeping this record helps you act fast and show diligence if questions arise.

Documented incident handling is part of a defensible governance record. It demonstrates that you monitor your AI and respond to problems — useful context if the Attorney General ever scrutinizes how a system was used.

TRAIGA does not require executive or board certification of an AI governance program — that was a feature of the original draft (HB 1709) that did not become law. We recommend documenting leadership review anyway, because clear accountability strengthens a governance program.

A timestamped, attributed record that leadership has reviewed the inventory, risk reviews, controls, and disclosures shows the program has organizational backing. It is a governance artifact, not a statutory attestation.

Refreshing that review on a regular cadence — for example, annually — keeps leadership engaged and keeps your governance record current. This is best practice, not a TRAIGA obligation.