A federal judge ruled Monday that Workday must face claims its AI-powered hiring software illegally screens out job applicants based on disability and other protected traits, rejecting the company's argument that California anti-discrimination laws do not apply to recruitment decisions made for out-of-state employers. The decision keeps alive the first proposed class action to broadly challenge the algorithmic decision-making inside AI screening tools that have become standard at large U.S. companies.
US District Judge Rita Lin in San Francisco denied Workday's bid to toss recent amendments to the lawsuit, ruling that because the company allegedly directed unlawful conduct from its California headquarters, it could be held liable under state law. The proposed class action, first filed in 2023, takes aim at the automated filtering logic that large employers increasingly rely on to narrow applicant pools.
A first-of-its-kind case
The lawsuit is the first of its kind to broadly target the algorithms underpinning AI screening software. Legal experts have noted that few cases have challenged employers' use of these tools so far, partly because job applicants often do not know when AI filters their resumes and partly because litigating over opaque automated systems presents steep evidentiary hurdles.
Workday's screening tools belong to a broader category of AI for Human Resources that has drawn scrutiny from regulators and worker advocates alike. The case could help establish how courts handle discrimination claims when the alleged bias is embedded in third-party software rather than in direct human decisions.
How the algorithm allegedly screens out applicants
Judge Lin refused to dismiss a claim that Workday's software can weed out job seekers based on "proxy indicators" of disabilities and illness - such as gaps in employment history - in violation of the federal Americans with Disabilities Act. The plaintiffs argue that these automated filters effectively penalize applicants whose work histories reflect periods of illness or medical treatment.
The judge did dismiss a claim that the software discriminated against Asian American applicants, ruling that the plaintiffs failed to follow proper procedure when adding it to the lawsuit. Claims involving Black job seekers, women, and people older than 40 remain active in the case.
Workday pushes back
Workday denied the allegations in a statement. "Our technology looks only at job qualifications, not protected traits like race, age, or disability. We rigorously test our products as part of our Responsible AI program to confirm our tools do not harm protected groups," the company said. Workday also maintained that its AI recruiting tools do not make hiring decisions "in California or anywhere else."
The plaintiffs' lawyers did not respond to requests for comment.
AI adoption in hiring outpaces regulation
Numerous surveys have found that more than 80% of U.S. employers, and virtually all Fortune 500 companies, use AI tools in the hiring process. Government agencies such as the Equal Employment Opportunity Commission have issued guidance warning that AI tools can replicate existing biases when they are trained on data reflecting past discrimination.
Despite widespread adoption and regulatory concern, litigation remains rare. Experts attribute the gap to low awareness among rejected applicants and the difficulty of proving causation when decisions flow through proprietary algorithms.
Why this matters for HR professionals
HR managers who evaluate or recommend AI screening vendors should audit how those tools handle employment gaps and other data points that could function as proxies for protected characteristics. Asking vendors to explain what signals their models treat as negative - and whether those signals correlate with disability, age, or race - is no longer a theoretical exercise. It is a legal exposure that courts are beginning to take seriously. HR professionals responsible for procurement and compliance may want to explore the AI Learning Path for HR Managers to build the technical literacy needed to assess vendor claims independently.
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