AI, media and liability: why PR and comms teams can't rely on generic E&O anymore
AI now sits in the middle of how content gets drafted, edited, and shipped. That's useful for speed, but it also widens the target for legal and reputational hits.
As Alexander Blair-Johns, CEO of Signal Underwriting, puts it, "the rise of AI-created and AI-assisted content has fundamentally changed the media E&O landscape." You feel it in day-to-day work: more outputs, tighter turnarounds, and fewer human checkpoints before something goes live.
What's changed for PR and comms leads
- Volume multiplies risk. One prompt can produce dozens of variants. A small mistake can echo across blogs, socials, newsletters, and pitches in minutes.
- Ownership gets murky. "These tools significantly increase the potential for accidental intellectual property infringement in both text and graphic-generated content," Blair-Johns warns. Tracking what's original vs. derivative gets harder as outputs stack up.
- Accuracy slips travel fast. "AI is not infallible: we've seen cases where factual errors are replicated and amplified when organizations rely heavily on these systems." Wrong dates, misattributed quotes, or mislabeled images can propagate across channels before anyone notices.
- Real-world example. In a widely reported incident, an AI-generated image of an accused trafficker was shown at a high-profile press conference as supposed proof of surrender, later debunked as fake. That's the kind of moment that turns a content shortcut into a credibility problem.
Why generic E&O often misses the mark
Traditional professional liability forms weren't built for publishing at scale. They can leave gaps exactly where AI-assisted workflows create pressure.
Blair-Johns is blunt: "Traditional E&O wordings lack the comprehensive coverage that media E&O policies provide for exposures like public disclosure of private facts, intrusion, and interference with rights of privacy or publicity." In practice, that includes:
- Public disclosure of private facts - publishing sensitive personal info the audience didn't need to know. See a plain-language overview from Cornell Law's LII here.
- Intrusion upon seclusion and right of publicity - collecting content in ways that feel invasive, or using someone's identity in a way they didn't approve. LII's entry on publicity rights is useful context here.
Media-focused policies are built around defamation, privacy, IP, takedowns, and reputational harms tied to publishing, broadcasting, and distribution. That's the coverage pattern AI-heavy content teams actually need.
Practical controls you can implement this week
- Human-in-the-loop. Require a named reviewer for every AI-assisted asset before publication. No exceptions for "small" posts.
- Source logging. Save prompts, model versions, and links to references. If a claim lands, you'll need proof of process.
- IP safety net. Run image/text checks for similarity before publishing. Avoid style mimicry of identifiable artists, authors, or brands.
- Fact layer. Separate generation and verification. Use a second tool or human to confirm names, dates, quotes, and image captions.
- Privacy filter. Block prompts that request or reveal non-public personal info. Redact private details by default.
- Rights clearance. Confirm licenses for any training add-ons, stock media, music beds, and fonts. Save the receipts.
- Corrections protocol. Pre-write your correction, retraction, and apology templates. Make the path to fix fast and public.
- Content recall. Keep an asset map so you can pull or update posts across all channels within hours, not days.
- Incident playbook. Define who investigates, who approves statements, and who speaks externally. Time kills trust.
- Team training. Teach prompt hygiene, bias checks, and IP awareness. The tool isn't the risk; unmanaged usage is.
Buying checklist: what to ask for in media E&O
- Explicit media perils. Defamation, public disclosure of private facts, intrusion, right of publicity, copyright/trademark infringement, false light, and misappropriation.
- AI-assisted content covered. No exclusions for content generated or edited with AI; clarity on "editorial control" standards.
- Takedown and correction costs. Coverage for retraction, withdrawal, and remediation (including paid boosts to correct the record).
- Crisis comms. Access to specialist counsel and PR support from day one, not after liability is established.
- Territory and platforms. Global distribution, social channels, podcasts, livestreams, newsletters, and syndication included.
- Sublicenses and vendors. Coverage extends to freelancers, agencies, and content partners acting on your behalf.
- Sublimits and carve-outs. Watch for low caps on privacy/publicity claims and exclusions tied to "knowing" violations.
- Retroactive date. Ensure prior acts are covered; AI content often gets republished or refreshed later.
- Defense outside limits (where available). So legal fees don't drain the pot meant for settlements.
What this means for your team
If AI sits in your content workflow, your risk profile has changed. Generic E&O assumes slower, manual production and narrower harms. That's not your reality anymore.
Blair-Johns' advice is clear: "Given these evolving risks, it's critical that media clients seek media E&O coverage specifically." Pair that coverage with tighter controls, and you'll protect both your legal position and your credibility when something slips.
Level up your team's AI workflow
If you need bite-sized training on prompt quality, fact-checking, and safe content generation for comms teams, explore curated options here: AI courses by job.
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