AI Bias In Hiring Is Real: What Mobley Case Means for Interview Coaching

On June 22, 2026, a federal judge ruled that the hiring platform Workday must continue  facing discrimination claims that its AI-powered HR software unlawfully rejected job applicants.

That means tens of thousands of job seekers who were rejected by companies using Workday’s tools may try to join the case. It also means that other states and courts are likely to look at this decision when they deal with discrimination complaints about AI hiring systems in the future.

Derek Mobley is a Black man over the age of 40 with a disability who applied to more than 150 positions at companies using Workday’s AI-powered hiring platform. He got a quick rejection every time. So fast, it seemed impossible that there was enough time between his application and rejection for human review. In February 2023, he filed a class action lawsuit that has become one of the most closely watched employment discrimination cases in the country.

If you coach job seekers, this case belongs in your awareness. Here is what it is, why it matters, and how it should shape the way we prepare clients for interviews.

The Mobley Case Explained

Workday is one of the most widely deployed HR technology platforms in the country. Its AI feature called Candidate Skills Match scores and ranks applicants before a recruiter ever sees them. Mobley’s lawsuit argues the system discriminates against people who are Black, over 40, or living with a disability, in violation of Title VII of the Civil Rights Act, the Age Discrimination in Employment Act, and the Americans with Disabilities Act.

What made this case landmark was a 2024 federal court ruling that Workday itself, the software vendor, could be held liable as an agent of its employer clients. That had never happened before. Software companies can now face legal consequences for discriminatory algorithms they build and sell.

What comes next is deep digging into how Workday’s AI treats real applicants, more job seekers joining the case, and employers rethinking how much they will choose to rely on “black box” hiring tools.

Is AI Bias in Hiring Real?

The Mobley case is the visible legal tip of iceberg that is AI bias in hiring.  For as long as AI screening tools have been used in hiring, there have been complaints that those tools demonstrate bias against protected classes of job seekers. In 2019, civil-rights advocates filed a high-profile FTC complaint against HireVue, claiming its use of Affectiva’s facial expression analysis in job interviews could discriminate against people with disabilities.  In response, the company discontinued using that particular technology.  (It is worth noting, however,  that other AI interview platforms continue to incorporate that technology.)  Similarly, CVS settled a case in 2024 after its AI video interviews allegedly rated candidates’ facial expressions for “employability”.

 And though companies may claim that the AI tools they use in interviewing reduce bias compared with human-led assessments, companies know that AI bias exists. In a 2024 ResumeBuilder survey of 948 business leaders, nearly half of those leaders acknowledged age bias in their AI hiring tools. A full quarter recognized that the tools perpetuate racial bias. 

They know that the AI tools they use in hiring demonstrate bias.  

Why Interview Coaches Need to Pay Attention

The Mobley case is a resume screening case. But similar AI algorithms are currently used in interviews. Increasingly, companies are employing AI to lead, transcribe, summarize, score and assess recorded job interviews.  Many companies use asynchronous AI-scored interviews at the start of the hiring funnel to validate application materials –  the resumes, cover letters, and work samples that are often themselves generated by AI. 

AI interview platforms may analyze vocal tone, word choice, response structure, and content – and then generate a transcript, summary, or report about the candidate’s suitability for the role. A human may or may not ever watch the recording. Some companies use AI as a silent co-pilot during human-led virtual interviews. An AI algorithm is present during human-led interviews, generating transcripts, summaries and scores in real time – even providing interviewers with feedback on what questions to ask next.

The research on what these AI systems actually measure to generate their assessments is troubling. A 2025 University of Melbourne study found that AI hiring tools struggled to accurately evaluate candidates with speech disabilities or non-native accents. And in March 2025, the ACLU filed a complaint against Intuit and its AI video interview vendor on behalf of an Indigenous, deaf applicant whose video response was analyzed for active listening skills.

You read that right. AI scored a deaf woman on active listening.

And here is the crux of why this is so problematic: A November 2025 University of Washington study found that human decision-makers who received AI-generated recommendations tended to mirror and amplify those biases rather than correct for them. The bias does not stay in the algorithm. It infects the product it generates and influences the people who use that product to make hiring decisions.

What This Means for How We Coach

Very few states have laws that require a candidate’s consent to use AI during a job interview.  Even fewer states require companies to disclose that AI is being used to assess a candidate’s interview responses. Our clients may not even realize that their interview is being scored by AI. Clients need to be prepared for the possibility that AI is in every interview space.  They have to know how perform well for the algorithm while they are also creating authentic connection with the human.  

First, help clients understand that the first assessor may not be human. Especially with large employers using platforms like Workday, the initial screening of a resume or a recorded video response may be entirely automated. This is not meant to alarm them. It is meant to help them prepare for who, or what, is in the room.

Second, correct a coaching myth that has been circulating: modern AI interview platforms do not work by matching exact keywords. They use natural language processing sophisticated enough to understand conceptual meaning. HireVue states explicitly on its website that there are no magic keywords to trick the system, because the NLP is reading for competency, depth, and substance, not specific phrases. What this means for your clients is more interesting than keyword-stuffing advice: vague, generic answers fail with these systems for the same reason they fail with a sharp human interviewer. The AI is looking for evidence, not vocabulary.

Third, structure matters. AI assessment platforms reward responses that have a clear logical arc: context, action, outcome. That through-line is what the system can parse and score. Candidates must deliver a structured answer, but a rigid STAR-formatted answer is not necessary to satisfy the algorithm. Any response that is specific, grounded in a real example, and moves clearly from situation through action to a defined result gives the system what it is looking for. How that is organized is less important than whether all the elements are there.

Fourth, name the equity issue when it is relevant. Candidates with non-native accents, speech disabilities, or other characteristics that do not fit the narrow profile these systems were trained on face a genuine disadvantage. That is not their failure. It is a documented flaw in the technology, increasingly supported by research and litigation. Where accommodations are available, encourage clients to request them before the interview. Where they are not, help clients practice until their delivery is as clear and confident as it can be, and remind them that these systems are not the final word.

Fifth, encourage clients to track their applications. The Mobley case began with one man noticing something was wrong across dozens of rejections. We are not attorneys, but we can help clients recognize patterns and know that legal protections and resources exist.

The Bigger Picture

Mobley v. Workday is not just a lawsuit. It is a data point confirming what many of us have observed for years: the algorithm is not neutral. It has absorbed the biases of its training data and is now encoding them into millions of hiring decisions at scale.

A parallel case filed in January 2026 against Eightfold AI adds another dimension, alleging the company collected and scored applicant data without consent in violation of the Fair Credit Reporting Act. This case may lead to better transparency about how AI is used in hiring, but the process is slow. And the technology is moving fast – your client may have an AI-assessed interview next Tuesday.

The Mobley case may ultimately reshape how AI hiring tools are built and held accountable. That is worth knowing, worth talking about with clients, and worth folding into how we coach.

Sources

Mobley, et al. v. Workday, Inc., Case No. 23-CV-00770 (N.D. Cal.) | Duane Morris Class Action Defense Blog, June 2, 2026 | Electronic Privacy Information Center v. HireVue FTC Complaint, 2019 | SHRM: HireVue Discontinues Facial Analysis Screening, 2021 | University of Washington (2024, 2025) | University of Melbourne (2025) | HireVue AI in Hiring Statement | ACLU Colorado / Intuit HireVue Complaint, March 2025 | Brookings Institution, April 2025 | HR Executive | AI Governance for HR | Smart Eye / Affectiva Acquisition, 2021