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

TRAIGA requires covered organizations to maintain a structured register of all AI systems deployed in consequential decisions. The inventory must document the system's purpose, the decisions it influences, the data it processes, the vendor (if third-party), and the oversight mechanisms in place.

The inventory is the foundation of TRAIGA compliance. Without it, there is no basis for risk assessment, no disclosure to generate, and no governance program to certify. Regulators expect the inventory to be current, organized, and producible on request.

An AI system inventory is not a one-time exercise. As organizations deploy new AI tools — especially in fast-moving clinical, HR, and operational contexts — the inventory must be updated to reflect the current AI portfolio.

TRAIGA requires a documented risk assessment for each covered AI system. The assessment must evaluate the potential harms the system could cause, the probability of those harms, the affected population, and the oversight controls that mitigate identified risks.

Risk assessments under TRAIGA are not informal reviews. They require structured documentation that can withstand regulatory scrutiny — a questionnaire-style evaluation with defined risk factors, a resulting risk classification, and a documented basis for that classification.

Risk assessments must be repeated on a defined schedule and whenever material changes are made to the AI system, its data inputs, its use case, or its deployment context. A static, one-time assessment does not satisfy TRAIGA's ongoing oversight requirements.

Based on the risk assessment, TRAIGA requires organizations to implement governance controls proportionate to the identified risks. For high-risk AI systems — particularly those making consequential decisions in healthcare, employment, credit, or housing — controls must include human oversight mechanisms, data governance procedures, and defined escalation paths.

Controls must be documented, assigned to responsible parties, and tracked for completion. TRAIGA does not accept good intentions as compliance evidence. Organizations must demonstrate that controls are actually implemented, with evidence of completion and regular review.

Controls are not static. As AI systems evolve and new risks are identified, the control framework must be updated. The ongoing control review process is itself a governance requirement under TRAIGA.

TRAIGA requires organizations to provide clear, accessible disclosures to individuals who are subject to consequential AI-driven decisions. Disclosure requirements include: notice that an AI system was used in the decision, a description of the AI system's purpose and general operation, the risk classification, the oversight mechanisms in place, and a contact point for questions or appeals.

Disclosures must be in plain language — not technical documentation. They must be proactively provided to affected individuals, not merely available on request. The format and timing of disclosures are specified by the regulation.

Disclosure obligations extend to third-party AI systems. If a vendor's AI tool is used in a consequential decision, the deploying organization — not the vendor — is responsible for providing the required disclosure to affected individuals.

TRAIGA requires organizations to maintain a structured log of AI incidents — instances where an AI system caused or risked causing unintended harm, produced a discriminatory outcome, failed in a material way, or was used outside its approved scope.

Incidents above a defined severity threshold must be reported to the relevant regulatory authority within a specified timeframe. Internal incident logs must capture the affected system, the nature of the incident, the severity assessment, the investigation process, and the remediation actions taken.

The incident reporting requirement creates a direct organizational accountability mechanism. Undisclosed or unrecorded incidents discovered during a regulatory investigation are treated as a more serious compliance failure than the incident itself.

TRAIGA requires designated organizational leadership — typically the CEO, CISO, or a board-level AI Governance Officer — to formally certify that the organization's AI governance program is in compliance with the regulation. This certification must be documented, timestamped, and retained as a governance artifact.

Executive certifications are not symbolic. They create personal accountability for the accuracy of the compliance attestation. Leadership must have reviewed the governance program — the inventory, risk assessments, controls, and disclosures — before certifying.

Certifications must be renewed on a defined schedule, typically annually. A lapsed certification is a compliance gap regardless of how well the underlying governance program is maintained.