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Texas TRAIGA (HB 149): a builder's guide

Informational only — not legal advice. Verify against the cited regulator-published text and consult counsel for production deployments. See AI-DISCLOSURE.md in this package.

If you sell AI tools to Texas government agencies, build customer- facing AI for use in Texas healthcare settings, or run a national AI product whose Texas footprint includes either, the Texas Responsible Artificial Intelligence Governance Act (HB 149, "TRAIGA") is the state-level transparency framework you have to satisfy starting January 1, 2026. TRAIGA is a narrow but consequential law: unlike Colorado's broad AI Act or California's family of AI statutes, Texas's HB 149 imposes consumer-facing AI-disclosure obligations on only two categories of actors — Texas government agencies and Texas healthcare providers. Get either category right and you've covered most of TRAIGA's footprint. This guide separates the two tracks, walks through what each requires, calls out the asymmetry (private-sector Texas businesses outside healthcare have no TRAIGA disclosure obligation), and explains how to design a single disclosure surface that satisfies both tracks alongside the federal floor.

What TRAIGA actually does

The Texas Responsible Artificial Intelligence Governance Act (HB 149, 89th Legislature) was signed by Governor Abbott on June 22, 2025 and takes effect January 1, 2026. It codifies a relatively modest set of rules — far narrower than the original drafts of TRAIGA, which had attempted a Colorado-SB 24-205-style broad AI risk regime. The final law has two operative consumer-disclosure provisions plus governance / civil- penalty provisions:

  1. § 552.058 (or as enacted) — Government-agency AI disclosure. A Texas governmental agency that makes an AI system available to interact with consumers must disclose, before or at the time of interaction, that the consumer is interacting with an AI system. Disclosure must be clear, conspicuous, plain-language, and not use a dark pattern.
  2. § 552.057 (or as enacted) — Healthcare-provider AI disclosure. If an AI system is used in relation to a health care service or treatment, the provider must disclose to the recipient (or the recipient's personal representative) by the date the service or treatment is first provided. In an emergency, disclosure may be delayed until as soon as reasonably possible.

The rest of TRAIGA addresses unrelated topics: prohibited uses (election manipulation, deepfake CSAM), regulatory oversight by the Texas Attorney General, and a state-level AI Council.

Track 1: government-agency disclosure

Who is covered

A "governmental agency" under TRAIGA tracks the Texas Government Code's standard definition: state agencies, departments, commissions, boards, and political subdivisions (counties, municipalities, school districts) — anyone exercising authority on behalf of the State of Texas or a political subdivision.

In scope:

Out of scope:

What counts as a sufficient disclosure

The statute requires disclosure that is:

Requirement Practical meaning
Clear The disclosure must be unambiguous — a reasonable person reads it and understands they're talking to an AI.
Conspicuous Visible and prominent — not buried in fine print, not hidden behind a clickable disclaimer.
Plain language No legalese, no jargon. "AI assistant" rather than "automated cognitive system."
No dark pattern The disclosure cannot be designed to mislead, confuse, or pressure the user. Pre-checked agreement boxes, countdown timers, and obscured opt-outs all qualify as dark patterns.
Timing "Before or at the time of interaction." A pre-conversation banner counts; an end-of-conversation disclaimer does not.

Plain-language template:

"You are interacting with an artificial intelligence system, not a person. To speak to a human agent, please [contact info]."

Common failure patterns for the government track

Track 2: healthcare-provider disclosure

Who is covered

A "healthcare provider" under TRAIGA includes:

The trigger is AI used in relation to a health care service or treatment. That language is broad and intentional. It includes:

What counts as a sufficient disclosure

The statute requires:

The statute does not specify a precise format. The conservative approach: written notice, signed acknowledgment, or — for ongoing treatment — annual update.

Plain-language template:

"An artificial intelligence system is being used to assist with your care. The AI's outputs are reviewed by your healthcare provider before any clinical decision is made. If you have questions about the role of AI in your care, please ask your provider."

Common failure patterns for the healthcare track

Where TRAIGA stacks with other federal and state rules

TRAIGA is a state-level floor for Texas AI deployment. It stacks with everything else.

Federal floors that always apply alongside TRAIGA

State-level overlays for cross-state Texas operators

A national health system with Texas operations also faces:

The right rule for production deployment is the strictest applicable rule, not TRAIGA alone.

TRAIGA's deliberate scope: what it does NOT cover

Understanding what TRAIGA leaves alone is as important as understanding what it covers. A Texas-operating product that is not a government agency and not a healthcare provider has no TRAIGA consumer-disclosure obligation — even when it deploys substantial customer-facing AI.

Examples NOT covered:

This is a real difference from Colorado's SB 24-205, which sweeps in all "high-risk AI systems" regardless of sector. TRAIGA's scope is narrower by design.

How TRAIGA is enforced

The Texas Attorney General has primary enforcement authority. HB 149 authorizes:

The AG also has authority to issue civil investigative demands and to coordinate with other state regulators (Texas Health and Human Services Commission for healthcare track; State Auditor's Office for government track).

How plainstamp helps

plainstamp ships two TRAIGA rules: us-tx-traiga-government-disclosure (Track 1) and us-tx-traiga-healthcare-disclosure (Track 2). Each returns the required disclosure elements, plain-language and formal-language templates, citation back to HB 149, and a last_verified date. Lookup:

# Government agency
npx plainstamp lookup --jurisdiction us-tx \
                      --channel live-chat \
                      --use-case government-services

# Healthcare provider
npx plainstamp lookup --jurisdiction us-tx \
                      --channel about-page \
                      --use-case healthcare

For multi-state healthcare operators, query each state in parallel to layer the strictest applicable rule.

The minimum viable compliance posture

If your Texas-operating AI deployment is starting from zero on TRAIGA, ship these four artifacts in order:

  1. Determine your track. Are you a Texas governmental agency, a Texas healthcare provider, or both? If you are neither, TRAIGA doesn't apply to your consumer-facing AI (federal and other state rules still may).
  2. Disclosure language deployed to all consumer-facing AI surfaces. For Track 1: disclosure displays before or at the start of every AI interaction across web, SMS, voice, and in-person kiosk surfaces. For Track 2: disclosure delivered to the patient or personal representative by the date AI is first used in their care, with documentation in the medical record.
  3. Vendor-procurement coordination. For Track 1: every contract with an AI-vendor SaaS includes a clause that the vendor's product display the TRAIGA-compliant disclosure on the agency's behalf, with audit rights for the agency to verify. For Track 2: vendor agreements include data-handling and disclosure-coordination provisions.
  4. Records. Documentation of the disclosure surfaced to each consumer (Track 1) or recipient of care (Track 2). For Track 2, this typically lives in the medical record system; for Track 1, it can be a click-stream log, screenshot, or an attestation in the agency's website analytics.

Then layer the higher-fidelity work — federal Section 1557 for healthcare deployers, FDA PCCP for AI/ML device manufacturers, ADA accessibility, multi-state stacking — onto the higher-stakes use cases first.

Source-of-truth links

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