AI Hiring and Firing Tools: Can an Algorithm Wrongfully Terminate You?

More companies than ever let software decide who gets hired, who gets promoted, and who gets cut. Resume screeners rank applicants, productivity dashboards flag underperformers, and predictive models recommend who to include in the next round of layoffs. When one of those systems decides your fate and you lose your job over it, the experience can feel impersonal and arbitrary. The legal question is whether it was also illegal, and that is where wrongful termination lawyers in Dallas are starting to see a new kind of case. An algorithm cannot be sued, but the employer that relied on it can be held responsible for the outcome.

Texas remains an at-will state, so a company can use whatever tools it likes to manage its workforce. What it cannot do is use those tools to reach a result the law forbids. A firing driven by software is judged the same way as a firing driven by a manager. If the decision turns on age, race, sex, disability, or another protected characteristic, swapping a human for a machine does not make it legal.

How an Algorithm Ends Up Discriminating

These tools rarely set out to discriminate. The trouble usually comes from the data they learn from. A model trained on a company’s past decisions absorbs whatever bias was baked into those decisions. If a firm historically promoted younger workers or pushed out employees after they took medical leave, an algorithm trained on that history can quietly reproduce the pattern while looking perfectly neutral on the surface.

The federal Equal Employment Opportunity Commission has been clear that automated tools count as a selection procedure under Title VII, the same category as any other employment test. That means a tool producing a disproportionate effect on a protected group can create disparate impact liability unless the employer shows it is job related and consistent with business necessity, and that no less discriminatory alternative was available. The EEOC uses a four-fifths rule of thumb: if the selection rate for one group falls below 80 percent of the rate for another, that gap can be evidence of discrimination. A productivity model that flags older workers for termination at twice the rate of younger ones raises exactly this concern.

Disability cases follow a parallel track. A tool that screens out applicants with gaps in employment, or one that penalizes a worker whose output dropped during a period of accommodation, can run afoul of the Americans with Disabilities Act. The duty to provide reasonable accommodation does not disappear because a computer made the call.

The Employer Cannot Hide Behind the Vendor

A common defense is that the software came from an outside company, so any flaw belongs to the vendor. The EEOC rejects this. An employer can be liable for discriminatory outcomes produced by a third-party tool it chose to use. Buying the product does not transfer the legal responsibility for how it affects your workforce. For a fired employee, this matters: the claim runs against the employer that deployed the system, not the distant company that built it.

What Texas Law Adds in 2026

Texas now has its own statute on the books. The Responsible Artificial Intelligence Governance Act, known as TRAIGA, took effect January 1, 2026, and it prohibits developing or deploying an AI system with the intent to unlawfully discriminate against a protected class. The law stakes out a narrow position compared to other states. It is built on intent, and it specifically says that disparate impact alone is not enough to establish a violation. Enforcement rests with the Texas Attorney General, there is no private right of action, and employers get a 60-day window to cure problems, with penalties reaching into six figures per violation.

For someone who lost a job to an algorithm, the practical takeaway is that TRAIGA is not the avenue for a personal lawsuit. The stronger path for an individual claim usually runs through the established federal and state anti-discrimination laws, Title VII, the ADA, the Age Discrimination in Employment Act, and Chapter 21 of the Texas Labor Code, where disparate impact remains actionable and where a fired worker can sue directly.

Building a Case Around an Automated Decision

Proving one of these claims takes more than a hunch that the software was unfair. The evidence often lives in records most workers never see: how the tool scored people, what data it weighed, how the outcomes broke down across protected groups, and whether comparable employees outside your group were treated differently. Much of this becomes available only through the legal process, which is one reason an early case review matters. Deadlines are short, generally 180 or 300 days to file a discrimination charge depending on the agency, and the documentation can be hard to preserve once you have left.

If you suspect an automated system played a role in your firing, the wrongful termination lawyers in Dallas at The Mundaca Law Firm can examine how the decision was made, identify which laws apply, and pursue the evidence that turns a suspicion into a claim. A firing dressed up as a neutral data point is still a firing, and you have the right to ask whether it was lawful.