BONUS!

Go Fact Yourself: Smart Questions About AI in PR

How is AI used in public relations?

AI is increasingly common in public relations workflows, especially for tasks that are repetitive, research-heavy or time-sensitive. For many public relations teams, AI acts as a support tool that improves efficiency and speeds up early-stage creative work.

Some common uses for AI in PR include:

  • Drafting first versions of press releases, pitches and social copy
  • Brainstorming campaign angles and content ideas
  • Organizing and refining media lists
  • Monitoring news trends and online conversations
  • Summarizing research, interviews or meeting notes
  • Assisting with content calendars and workflow organization
  • Generating headline or subject line variations

That said, AI still requires strong human oversight. It can help generate ideas quickly, but it can’t tell the good ones from the bad, and it doesn’t understand nuance, timing, audience emotion or cultural context in the same way experienced communicators do.

What are the risks of AI-generated PR content?

AI-generated content can be useful, but relying on it too heavily creates several potential risks for brands and organizations.

One major concern is accuracy. AI tools can occasionally generate false or misleading information, sometimes referred to as “hallucinations.” In PR, where credibility matters deeply, even small inaccuracies can damage trust.

Other risks include:

  • Messaging that feels generic or overly polished
  • Content that lacks emotional depth or authenticity
  • Misunderstanding cultural context or sensitive topics
  • Repetitive brand messaging that sounds interchangeable
  • Inconsistent tone or brand voice
  • Publishing inaccurate information without proper fact-checking

There’s also the issue of audience perception. People are becoming increasingly aware of AI-generated communication, and many can sense when messaging feels overly manufactured or impersonal.

Who’s Responsible When AI Gets Something Wrong?

AI can generate content quickly, but it can’t take responsibility for the accuracy, tone or impact of that content. That responsibility still belongs to the people and organizations using the tool. And in public relations, credibility matters.

A misleading statistic, an inaccurate statement or messaging that misses important context can damage trust quickly, especially in fast-moving news cycles.

Technology can assist the process, but accountability still belongs to people.

Why Does AI Writing Sometimes Feel So Empty?

AI-generated writing can often sound polished on the surface while still feeling strangely hollow. AI systems, particularly large language models (LLMs), are designed to predict patterns in language and generate content based on patterns and probabilities, not communicate from lived experience, emotion or genuine perspective.

The writing that resonates most with people usually reflects something human behind it: insight, vulnerability, humor, instinct, emotion or original thought. AI can mimic those qualities to a degree, but it can’t genuinely experience them.

That’s why so much AI-generated content feels interchangeable. It may be technically polished, but it lacks the perspective that gives communication personality and meaning.

In public relations, that distinction matters. Audiences don’t just remember information. They remember stories, emotion, and authenticity.

Should PR Teams Disclose When They Use AI?

In most cases, disclosure depends on how AI’s being used. Using AI to brainstorm headline ideas or organize notes is different from publishing AI-generated content with minimal human review.

The guiding principle should be transparency. If AI plays a meaningful role in creating public-facing communication, PR teams should carefully consider if disclosure is appropriate.

The goal isn’t to announce every tool used behind the scenes. It’s to protect trust. If using AI would change how an audience understands the message, disclosure deserves serious consideration.

Do Journalists Trust AI-Generated Pitches?

Generally, journalists care less about whether AI helped with a pitch and more about whether the pitch is useful, accurate and relevant. The problem is that AI-generated pitches often make bad habits easier to scale.

A generic pitch is still generic even when it’s written faster. If AI’s used to spray broad, impersonal outreach across a media list, it can damage relationships quickly. Journalists already receive more irrelevant pitches than they can handle, and AI can make that noise worse.

A strong media pitch still needs:

  • A relevant story angle
  • A clear understanding of the journalist’s beat
  • Accurate information
  • Timely context
  • A human reason for why the story matters

AI can help draft or refine a pitch, but it shouldn’t replace the judgment that makes outreach thoughtful. The best pitches still feel specific, informed and respectful of the person receiving them.

Is AI Making PR More Efficient, or Just Noisier?

Both are possible.

AI can absolutely make PR teams more efficient, but efficiency becomes a problem when it turns into unchecked volume. More content and more pitches don’t automatically make for better communication—especially if every brand starts producing more of the same.

The real question isn’t whether AI helps PR teams move faster. It’s whether that speed is being used to create better work.

When AI supports thoughtful strategy, it can be valuable. When it simply helps teams produce more generic output, it adds to the noise.

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