Mobley v. Workday Class Action Expands, Putting 10,000+ Employers in Liability Crosshairs
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The News
The Mobley v. Workday class action has intensified through 2026. On 6 March, Judge Rita Lin rejected Workday's argument that the Age Discrimination in Employment Act does not cover job applicants, clearing a major procedural hurdle. On 16 May, the court allowed the case to proceed as a class action. Plaintiffs allege that Workday's AI-powered screening tools unlawfully filtered out applicants based on age, race, and disability. The court's treatment of Workday as an "agent" of the employer means both the vendor and the 10,000+ employers using Workday's hiring tools face compounding liability. Separately, a January 2026 class action against Eightfold AI argues that AI-generated applicant scores function as "consumer reports" under the Fair Credit Reporting Act, adding consumer privacy and transparency dimensions to the discrimination claims.
Why It Matters
This case establishes that employers cannot deflect liability onto their AI vendors. If a third-party screening tool makes a discriminatory decision, both the vendor and the employer are exposed. For TA leaders, the practical implication is stark: "the algorithm did it" is not a legal defence. The EEOC has made algorithmic fairness a priority under its 2024-2028 Strategic Enforcement Plan, and the four-fifths rule remains the benchmark for measuring disparate impact. Employers who cannot explain how their screening tools make decisions — or produce evidence of bias testing — are carrying unquantified risk.
Taking Action
All action is situated in your corporate context. These are starting points, not prescriptions — choose what fits.
Connect
Who to talk with in your enterprise
Your general counsel and your head of talent acquisition. GC needs to know which AI tools are in your hiring stack and what vendor representations exist about bias testing and disparate impact. The TA head needs to ensure that no automated rejection is sent without documented human review — a rubber-stamp approval will not meet the standard the EEOC and courts are setting.
Inspect
What to take a closer look at
For each AI-powered screening tool in your stack, request the vendor's most recent bias audit. If they cannot provide one, or if it is more than 12 months old, that is a material risk. Then check whether your process includes meaningful human review before any automated rejection — not a nominal sign-off, but a reviewer with the authority and competence to override the system.
Reflect
What to think about more deeply
If your CEO asked you tomorrow whether your hiring algorithm could discriminate against older candidates, would you answer with evidence — or with a vendor's assurance?