Hiring Market Trends: The Workday Lawsuit

A landmark lawsuit is working its way through the federal courts; here's what's happening, in plain English.

The story starts with one man and over 100 rejections.

Derek Mobley is a Black man over 40 who lives with anxiety and depression. Starting in 2017, he spent years applying to more than 100 jobs through companies that all used the same HR software platform: Workday. He was rejected every time, often within minutes, sometimes with automated emails arriving at 1:30 in the morning. The speed and consistency of the rejections made him suspect something wasn't right. No person, he reasoned, could be reviewing and rejecting applications that fast. He was right. In 2023, rather than suing the companies that rejected him, he sued the software company behind each rejection: Workday. That case, formally known as Mobley v. Workday Inc., has become the most closely watched AI hiring lawsuit in the United States.

What is Workday?

Workday is one of the most widely used HR software platforms in the world. More than 80% of U.S. employers, and nearly every company in the Fortune 500, now use hiring tools like these. That means that many candidates are screened, at least in part, by an algorithm before a human ever sees the application. Workday's platform includes resume screening, candidate ranking, and skills-matching software. The lawsuit argues these tools function as gatekeepers, making consequential decisions about who gets considered and who gets quietly filtered out.

What exactly is Workday being accused of?

The core of the lawsuit is what lawyers call "disparate impact", meaning the algorithm produced discriminatory outcomes against protected groups, even without anyone explicitly programming it to do so. Workday's software was specifically accused of screening candidates using proxies like employment gaps and patterns that read like recurring medical leave; so while not a single company's HR manual says "reject cancer survivors," these proxy measures have been used to screen out applicants that organizations see as burdens based on predictions about patterns. AI has now put these patterns to work, silently, at scale. The plaintiffs argue the algorithm disproportionately screened out Black applicants, people over 40, and people with disabilities — not through intentional bias, but because it was trained on decades of hiring data that reflected those biases to begin with.

What did the court decide?

Workday tried to argue that it just makes the software and that employers make the actual hiring decisions, so Workday shouldn't be liable. Judge Rita Lin rejected these claims outright, letting the discrimination claims move forward, partly because Workday builds, trains, and runs these tools out of its California headquarters. On June 22, 2026, the court confirmed the core discrimination claims can proceed. This is significant and signals that courts are increasingly willing to hold technology vendors accountable for the outcomes their tools produce, not just the employers using them.

What does this mean in practice?

Beyond the legal specifics, the broader implication is that discrimination in automated hiring got trackable. A decade ago, a qualified candidate could have been turned away by a hundred employers: slowly, by a hundred different people in a hundred different offices, each rejection its own small story, none of them obviously connected. These rejections were spread thin across years and HR departments, and slow enough that no one had to notice the pattern. One system applying one logic to everyone, instantly, is what brings that pattern into focus.

The next phases of this lawsuit will surely have broad ripple effects through the many industries using Applicant Tracking Systems and the AI tools within them.