Texas Responsible AI Governance Act (TRAIGA): requirements, deadlines and compliance actions

A governmental agency that makes an AI system available to interact with consumers must disclose to each consumer, before or at the time of the interaction, that they are interacting with an AI system. The disclosure is owed even where the AI nature of the interaction would be obvious, must be clear and conspicuous, written in plain language and may not use a dark pattern; a hyperlink to the disclosure is acceptable for online services.

Practical action: Put a plain-language AI notice at the entry point of every public-facing chatbot, voice line or automated service and keep a screenshot record.

Evidence examples: AI interaction disclosure copy and placement record

Framework mapping (original, editorial): NIST AI RMF 1.0 GOVERN 5.1, MANAGE 4.1; ISO/IEC 42001:2023 Annex A.8.5

Open the obligation page →Business and Commerce Code Section 551.051 Verified 26 Sep 2026 (a factual check against the official source, not a legal review)

A person who provides health-care services or treatment and uses an AI system in relation to those services must disclose that use to the patient, or to the patient's personal representative or guardian, no later than the date the service or treatment is first provided, with an exception for emergencies where the disclosure is made as soon as reasonably possible. The disclosure must be clear, conspicuous and in plain language.

Practical action: Add an AI-use statement to intake and consent materials for services that use AI, with an emergency-follow-up rule.

Evidence examples: Patient AI-use disclosure in intake or consent documents

Framework mapping (original, editorial): NIST AI RMF 1.0 GOVERN 5.1, MANAGE 4.1; ISO/IEC 42001:2023 Annex A.8.5

Open the obligation page →Business and Commerce Code Section 551.051 Verified 26 Sep 2026 (a factual check against the official source, not a legal review)

A person may not develop or deploy an AI system in a manner that intentionally aims to incite or encourage a person to commit physical self-harm, including suicide, to harm another person, or to engage in criminal activity. The prohibition turns on the developer's or deployer's intent rather than on the system's effects, which is the pattern followed throughout the Act's prohibited-use provisions.

Practical action: Record the intended purpose of each system at design review and add safety testing for self-harm and violence content in conversational products.

Evidence examples: Intended-purpose statement and prohibited-use screening record; Safety evaluation for self-harm and violence content

Framework mapping (original, editorial): NIST AI RMF 1.0 GOVERN 1.1, MAP 1.1, MEASURE 2.6; ISO/IEC 42001:2023 Annex A.9.4, A.6.1.2

Open the obligation page →Business and Commerce Code Section 551.052 Verified 26 Sep 2026 (a factual check against the official source, not a legal review)

A governmental entity may not develop or deploy an AI system that evaluates or classifies natural persons or groups on the basis of their social behaviour or personal characteristics, with the intent to calculate or assign a social score or similar valuation that leads to detrimental or unfavourable treatment unrelated to the context in which the data was collected, or that is unjustified or disproportionate to the behaviour.

Practical action: Screen agency scoring, eligibility and risk-ranking tools for social-scoring characteristics before procurement or build.

Evidence examples: Prohibited-use screening record for scoring tools

Framework mapping (original, editorial): NIST AI RMF 1.0 GOVERN 1.1, MAP 1.1; ISO/IEC 42001:2023 Clause 6.1.4; Annex A.5.2

Open the obligation page →Business and Commerce Code Section 551.053 Verified 26 Sep 2026 (a factual check against the official source, not a legal review)

A governmental entity may not develop or deploy an AI system for the purpose of uniquely identifying a specific individual using biometric data, or of gathering images or other media from the internet or another public source without the individual's consent, where doing so would infringe a right guaranteed under the United States or Texas constitutions or violate state or federal law. The Act preserves lawful uses that comply with existing biometric-privacy law.

Practical action: Require legal sign-off on lawful basis and constitutional review before any agency biometric-matching or public-image scraping project.

Evidence examples: Legal review of biometric AI use

Framework mapping (original, editorial): NIST AI RMF 1.0 GOVERN 1.1, MEASURE 2.10; ISO/IEC 42001:2023 Annex A.5.2, A.7.3

Open the obligation page →Business and Commerce Code Section 551.054 Verified 26 Sep 2026 (a factual check against the official source, not a legal review)

A person may not develop or deploy an AI system with the intent to unlawfully discriminate against a protected class in violation of state or federal law. A disparate impact on a protected class is not, by itself, sufficient to show an intent to discriminate, and insurers and financial institutions acting under their own regulatory regimes are treated separately.

Practical action: Document the non-discriminatory purpose of each decision system and keep fairness testing evidence that shows there was no intent to discriminate.

Evidence examples: Purpose statement and fairness testing record

Framework mapping (original, editorial): NIST AI RMF 1.0 MEASURE 2.11, MANAGE 1.3; ISO/IEC 42001:2023 Annex A.6.1.2, A.9.4

Open the obligation page →Business and Commerce Code Section 551.056 Verified 26 Sep 2026 (a factual check against the official source, not a legal review)

A person may not develop or distribute an AI system with the sole intent of producing, assisting or aiding in producing, or distributing child pornography or unlawful deep-fake videos or images, including sexually explicit deepfakes of a person without consent, or of engaging in sexually explicit text-based conversations while impersonating or imitating a child, in violation of the Texas Penal Code.

Practical action: Enforce content-safety filters and abuse-detection on generative products and record the intended purpose of any image or chat model at release.

Evidence examples: Content-safety policy and filter test results; Prohibited-use screening record

Framework mapping (original, editorial): NIST AI RMF 1.0 GOVERN 1.1, MEASURE 2.6, MANAGE 2.3; ISO/IEC 42001:2023 Annex A.9.4

Open the obligation page →Business and Commerce Code Section 551.057 Verified 26 Sep 2026 (a factual check against the official source, not a legal review)