Can Texas employers use AI to screen job applicants?
Yes, and the liability for what it does is yours, not the vendor’s. Disparate impact does not care who wrote the model.
Last updated: August 02, 2026
Direct Answer
Yes, Texas employers may use AI tools to screen applicants, but the employer remains responsible for the outcomes. Federal and Texas discrimination laws apply to AI-driven decisions exactly as they apply to human decisions, and the Texas Responsible AI Governance Act prohibits deploying AI systems developed with the intent to unlawfully discriminate against protected classes. Employers should vet vendors, keep human review in the process, and document how the tool is used.
Controlling authority: Title VII and the ADA, which govern by disparate impact regardless of intent, and TRAIGA (Tex. H.B. 149), which is intent-based and enforceable only by the Texas Attorney General.
Inventory automated rejection points and test pass-through rates
The legal system does not care whether a person or a model rejected the applicant. If an AI screening tool disproportionately filters out applicants over 40, applicants with disabilities, or applicants of a particular race or sex, the employer using the tool owns that disparate impact. Vendor marketing about bias-free algorithms transfers none of the liability.
Disability accommodation is the sharpest edge. Video interview scoring, personality assessments, and gamified screens can disadvantage applicants with disabilities in ways the employer never sees. The safe pattern is an advertised, easy accommodation path: a human alternative to any automated step, offered before the applicant has to fail the automated one.
| Source | What it does | What it does not do |
|---|---|---|
| Title VII and the ADA | Still the operative risk. Disparate impact liability attaches regardless of intent, and regardless of whether a vendor built the tool | It does not excuse you because the algorithm is a third party’s. |
| TRAIGA (effective 1 January 2026) | Prohibits developing or deploying AI with the specific intent to discriminate on protected characteristics, plus a narrow set of other prohibited uses | It is intent-based, not impact-based. It was pared back substantially before passage and imposes far less on private employers than commentary suggests. |
| TRAIGA enforcement | The Texas Attorney General only | There is no private right of action. Your TRAIGA exposure is regulatory, not litigation. |
| The four-fifths rule | The screen that will actually surface your problem | It is a triage indicator, not a safe harbour above 0.80. |
| EEOC AI technical assistance | Removed from the EEOC website on 27 January 2025 | Those were non-binding technical assistance documents. Removing them changed the explanation, not the obligation. Title VII and the ADA are untouched. |
| Your vendor contract | Allocates cost and cooperation between you and the vendor | It does not transfer liability to the vendor. The employer is the one that made the decision. |
What Employers Should Require From Vendors
Before deploying any screening tool, get answers in writing: what data trained the model, what adverse impact testing has been run and how recently, what the tool actually measures, and how the vendor supports accommodation requests. A vendor that cannot answer those four questions is selling you their liability.
Keep a human meaningfully in the loop, and document that the human can and does override the tool. Records of what the tool recommended, what the human decided, and why are the evidence that saves you when a rejected applicant files a charge.
| Requirement | What to ask for | Why |
|---|---|---|
| Adverse impact testing | Results by race, sex, ethnicity and age, on your applicant pool | A vendor’s aggregate testing says nothing about your population. |
| Validation evidence | Job-relatedness and business necessity, documented | This is the defence if impact appears. |
| What the model actually scores | The features and their weights, at least in summary | You cannot defend a decision you cannot describe. |
| Accommodation pathway | A documented alternative for candidates who cannot use the tool | An ADA obligation the vendor will not discharge for you. |
| Human review point | Where a person can override, and on what basis | A fully automated rejection is the hardest fact pattern to defend. |
| Audit and data rights | Your right to test, and to export your own data | Without it you cannot run the four-fifths screen at all. |
| Change notification | Notice before the model is retrained or changed | A silent model update can move your selection rates overnight. |
AI Screening Risks to Watch
AI hiring risk concentrates where nobody is watching the outcomes. Watch for these.
- No adverse impact analysis run on the tool's actual pass-through rates
- Automated rejections issued with no human review at any stage
- No accommodation alternative for disabled applicants
- Vendor contracts silent on bias testing and audit rights
- Nobody in the company able to explain what the tool measures
Run the four-fifths screen on your own applicant pool
Inventory every automated step between application and offer, including tools your ATS bundles in that you never chose. For each, identify what it filters on and pull the pass-through numbers by protected group if the volume allows.
Write down the human review step. If rejections flow straight from tool to candidate with no human touch, add one before an agency asks why there is none.
| Step | The calculation | Worked example |
|---|---|---|
| 1. Selection rate per group | Selected ÷ applicants, for each group | Group A: 60 of 100 = 60%. Group B: 30 of 100 = 30%. |
| 2. Identify the highest rate | The comparison base | Group A, at 60%. |
| 3. Compute the ratio | Lower rate ÷ highest rate | 30% ÷ 60% = 0.50. |
| 4. Apply the threshold | Below 0.80 is generally regarded as evidence of adverse impact | 0.50 is well below 0.80. This selection procedure needs examination. |
| 5. Do not stop at 0.80 | Smaller differences may still be adverse impact where statistically and practically significant, or where the employer’s conduct discouraged applicants disproportionately | A ratio of 0.85 is not a clean bill of health. |
| 6. If impact appears | Validate the procedure for job-relatedness and business necessity, or find a less discriminatory alternative | Document the analysis either way. The undocumented analysis is treated as no analysis. |
Job Description Reality Gap Scorecard
Scores the distance between what the job description says and what the person actually does.
When a screening tool shows disparity
Get help before deploying a new screening tool, because the vendor evaluation and the documentation framework are cheap at the start and expensive after a charge.
If you already use AI screening and have never tested outcomes, an HR audit that includes your hiring funnel closes the gap fastest.
Get a Straight Answer for Your Situation
General rules only go so far. If this question is live in your organization right now, talk it through with a senior HR consultant before you act. One conversation now costs less than one claim later.
Contact UsThis page provides general HR information for employers and is not legal advice. For legal interpretation or representation, consult qualified employment counsel.