Texas Responsible AI Governance Act (HB 1709)

Overview

Texas HB 1709, the Texas Responsible AI Governance Act, proposes the first comprehensive AI regulatory framework in Texas. The bill would require deployers of high-risk AI systems to use reasonable care to protect Texas consumers from algorithmic discrimination.

HB 1709 is closely modeled on Colorado SB 24-205 (the Colorado AI Act), which is currently the most detailed state AI law in the US. Texas would become the second state to enact a comprehensive, risk-based AI law if HB 1709 passes.

Important: This is a proposed bill, not current law. Monitor its status and prepare proactively — the bill is advancing and Texas AI regulation is likely regardless of whether HB 1709 passes in 2026.

Who It Applies To

HB 1709 would apply to deployers of high-risk AI systems that make or are a substantial factor in making consequential decisions about Texas consumers.

"Deployer" means a person doing business in Texas that deploys a high-risk AI system. This includes:

• Businesses headquartered anywhere that serve Texas customers
• Companies with Texas employees using AI in HR decisions
• Any organization using high-risk AI that affects Texas residents

Small business exemption: The bill includes scaled-down obligations for businesses with fewer than 25 employees or less than $5 million in annual revenue. Specific requirements TBD as the bill advances.

High-Risk AI Systems

A high-risk AI system under HB 1709 is any AI system that makes, or is a substantial factor in making, a consequential decision about an individual in these categories:

| Category | Examples | |---|---| | Employment | Hiring, promotion, termination, compensation | | Housing | Rental applications, mortgage, property insurance | | Credit & Lending | Loan approval, credit scoring, interest rates | | Education | Admissions, financial aid, academic evaluation | | Healthcare | Diagnosis, treatment recommendations, medication | | Insurance | Applications, underwriting, claims | | Legal Services | Legal representation or referrals |

A consequential decision is one that produces a material legal effect or similarly significant effect — including access to services, financial outcomes, or employment status.

Key Requirements

1. Impact Assessment

Before deploying any high-risk AI system, conduct an impact assessment documenting:

• Intended purpose and reasonably foreseeable uses
• Benefits of the system
• Known and reasonably foreseeable risks of algorithmic discrimination
• How the system was tested for discriminatory outcomes
• Transparency, explainability, and human oversight mechanisms
• How training data was collected, processed, and used

Impact assessments must be updated annually and on material changes.

2. Risk Management Program

Implement a written program for managing risks of algorithmic discrimination:

• Policies and procedures for high-risk AI governance
• Vendor due diligence (require developer documentation)
• Ongoing monitoring for discriminatory outcomes in production
• Employee training on the use of high-risk AI systems

3. Consumer Notifications

When high-risk AI makes a consequential decision:

• Notify the consumer that AI was used
• Explain in plain language how the AI influenced the decision
• Provide a meaningful opt-out mechanism
• If adverse: explain the basis for the decision

4. Annual Reporting

Annual report to the Texas Attorney General summarizing:

• High-risk AI systems deployed in the prior year
• Impact assessments completed
• Discrimination risks identified and mitigated
• Any instances of known algorithmic discrimination

Differences from Colorado AI Act

| Aspect | Colorado AI Act | Texas HB 1709 | |---|---|---| | Status | Enacted (effective June 30, 2026) | Proposed (pending enactment) | | Enforcement | Colorado AG, civil penalties | DTPA framework, AG enforcement | | Max penalty | $20,000 per violation | $10,000 per violation | | SMB exemption | Under 50 employees | Under 25 employees, less than $5M revenue | | Annual report | State agency | Texas AG | | Core framework | Risk-based, high-risk AI | Identical framework |

For most compliance purposes, building to the Colorado standard means you're substantially ready for Texas.

Legislative Status

As of April 2026:

• Introduced in Texas House (January 2026)
• Assigned to House Technology and Innovation Committee
• Passed committee with amendments (March 2026)
• Awaiting full House vote
• Senate companion bill (SB 2378) assigned to committee

The bill has significant industry opposition from tech trade groups arguing for federal preemption, but consumer advocacy groups and the Texas AG's office have signaled support. Legislative observers give it a 60-70% chance of passing the full legislature this session.

If passed, implementation would begin 18-24 months after the governor's signature.

How to Prepare

Even if HB 1709 doesn't pass in this session, Texas will likely pass AI legislation within 1-2 years. Take these steps now:

Step 1: Build to the Colorado Standard

Colorado AI Act compliance is the de facto national baseline. If you comply with Colorado, you're approximately 85% ready for Texas. Start with:

• Inventory all AI systems making consequential decisions
• Classify which are high-risk
• Build your impact assessment program
• Document your risk management practices

Step 2: Monitor the Bill

Subscribe to our newsletter for real-time updates on HB 1709 as it advances through the legislature. We'll alert you when the bill passes committee votes, floor votes, and reaches the governor.

Step 3: Engage Legal Counsel

Engage Texas-based legal counsel familiar with state AI regulation. The DTPA framework is Texas-specific, and the implications for enforcement are different from Colorado's approach.

Step 4: Map Your Texas Exposure

Identify all AI systems you deploy that affect Texas consumers or employees. Document which would be "high-risk" under HB 1709's categories. This inventory is the foundation of any compliance program.

Need help with compliance preparation? Browse AI governance consultants