PR, AI, and the New Information Order
An AI voice named Vega said the quiet part out loud: "I'm here to help, not replace." That sounds reassuring - until you notice how quickly AI is shaping what gets said, what gets noticed, and what gets lost.
For PR and Communications teams, this isn't theoretical. It affects your comment sections, your public meetings, your interviews, and your message discipline. Here's a clear-eyed view of what's happening and a playbook to respond.
The Comment Section Just Changed
AI-written comments are already flooding public threads. They read calm, balanced, and "reasonable." They also flatten voice and turn lived experience into algorithm-friendly prose.
Two issues for comms leaders: authenticity and influence. If bots steer the tone and conclusions of public discourse, you aren't talking with a community - you're tuning a feedback loop. That's not a debate; it's a simulation.
Public Meetings Without People
Newsrooms are leaning on AI to record, transcribe, and summarize hearings. Human review sounds like a safeguard, but time is limited and summaries tend to define the record. Details shared late, or in hallway conversations, vanish.
Result: AI quietly decides what counts. Not by malice, but by defaults and training data. Your outcomes depend on whether your key points are structured in ways machines surface first.
Interviews: General vs. Specific
Ask an AI to prep questions for a policymaker and you'll get committee lists, budget angles, and polite generalities. Useful, but shallow. What's missing are the local stakes, the uncomfortable specifics, and the context humans remember.
If media leans on AI prep, the burden shifts to you to inject precision. Don't rely on the interviewer to go there.
What This Means for PR and Communications
Your job now includes protecting human signal from machine noise. That starts with policy, process, and message design.
Policy: Set the Rules for Authenticity
- Require AI-use disclosure on owned channels (comments, community portals, submissions). No disclosure, no publish.
- Do not rely solely on AI "detectors." They're unreliable. Prioritize behavior signals (sudden tone/length shifts, volume spikes, off-hours bursts, uncanny "balanced" phrasing) and account verification.
- Label your own use of AI. Say where it was used (transcripts, summaries), where humans stepped in, and who is accountable.
- Adopt a provenance standard for content you originate or host. Explore C2PA for verifiable metadata on edits and authorship. Learn more.
Process: Design for Human Judgment
- Human-in-the-loop by default. Any AI summary that could influence public understanding gets human review, with named approvers.
- Escalation paths. If a topic touches safety, finance, elections, or legal risk, trigger a higher review tier.
- Incident playbook for astroturfing. Define thresholds (volume, velocity, similarity), evidence you'll collect, and response options (rate limits, temporary holds, visible labeling).
- Comment friction where needed. Require a short prompt about lived experience, location relevance, or stake in the issue. Bots struggle to answer convincingly at scale.
Message Design: Be Findable by Humans and Machines
- Front-load your point. AI summarizers overweight openings. Put the takeaway and numbers in the first 15-30 seconds or first two sentences.
- Structured redundancy. Restate the key point near the end so late-meeting summaries don't miss it.
- Provide the summary yourself. After hearings or briefings, publish a two-paragraph recap with a clear title, bullets, and source links. Journalists and models will copy your structure.
- Use quotable specificity. Names, places, dollar amounts, dates. Vague language gets compressed or dropped.
Media Relations in an AI-Prepped Newsroom
- Pitch with context, not just angles. Include 3 precise, locally relevant questions a human would ask - and the data behind them.
- Offer artifacts that survive summarization: executive quotes under 20 words, one chart, one comparison, and one stakeholder voice.
- Proactively send post-interview clarifications. Short, factual, and linkable. Reduce the odds that AI "fills in" gaps.
Community Management: Keep It Human
- Make transparency the norm. Visible badges for verified humans. Visible labels for AI-assisted posts.
- Moderate for sincerity and contribution, not polish. Real people are sometimes messy. That's a feature.
- Host periodic human-only AMAs with identity verification. Publish summaries with clear authorship.
Governance and Accountability
- Document your AI uses: what tools, for which tasks, who approves, what gets logged.
- Publish your ethics anchor. Borrow from journalism standards on accuracy, independence, and transparency. SPJ Code of Ethics is a good reference point.
- Review quarterly. Sunset tools or prompts that drift outcomes or mute dissenting voices.
Templates You Can Steal
Comment Disclosure Line
"This comment was assisted by AI for grammar and structure. The ideas and experiences are my own."
Owned-Channel AI Use Statement
"We use AI for transcripts and first-draft summaries. Human editors review and approve all published content. Questions? Email comms@yourorg.com."
Metrics That Matter
- Human contribution rate: % of comments/posts verified as human.
- Specificity index: ratio of posts with named facts (dates, amounts, locations) to total posts.
- Summary fidelity: variance between your issued recap and third-party summaries (spot-check monthly).
- Escalations per quarter: should trend down as policy hardens.
The Tension to Keep
AI can make discussion calmer and more "thoughtful." It can also sand off the parts that make public discourse real: experience, friction, and local nuance. Coexistence is possible, but only if humans set the rules and keep the pen.
Use AI as a tool. Guard human judgment like it's your brand - because it is.
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