Deploying AI in PR: Lessons From Building a Responsible Workflow
Artificial intelligence is now part of how we operate across accounts and disciplines. As a full-service marketing, PR and advertising firm based in Little Rock, our question was never "should we use AI?"-it was "how do we deploy it responsibly without risking trust, quality or client outcomes?"
Here's what we learned moving from scattered experiments to a clear, values-driven approach that actually improves work and preserves credibility.
From Ad Hoc Experiments to a Company Playbook
We began like many teams: individual pros testing generative tools for drafting, research and data tasks. The upside showed up fast-fewer blank pages, better summaries, tighter turnaround. So did the risks-accuracy, IP, and ethics.
That pushed us to formalize use. We studied how AI affects our client sectors, the regulatory questions in the mix, and the ethical guardrails we needed. The result was a responsible AI pledge and an internal framework we regularly update.
Principles That Protect Trust
- AI is an aid, not a replacement. Human expertise leads. Tools support judgment; they don't make it.
- Verification is mandatory. Every AI output gets fact-checked, source-checked and edited by a subject-matter pro.
- Client alignment is nonnegotiable. We only use AI where it improves outcomes for clients and stakeholders.
Where AI Delivers Value in PR and Communications
- Content development: Faster first drafts, outlines and reports. We transcribe interviews, summarize meeting notes, and repurpose long-form content into briefs or talking points-then refine messaging by hand.
- Research and monitoring: Quick scans across industry sources to spot trends and risks. We still analyze and interpret, which strengthens situational awareness on accounts.
- Process efficiency: Templated documentation, project coordination and repetitive admin get streamlined so teams can focus on strategy and creative problem-solving.
What We Got Wrong (and Fixed)
- Training builds confidence: Tools are only half the story. We needed education on ethics, data security, disclosure and IP-plus practical prompts and review checklists.
- Speed can't outrun rigor: Shortcuts introduce risk, even on routine tasks. We built review gates and clear ownership for final approvals.
- Policies must iterate: AI changes fast. We update tools, permissions and rules on a schedule and after every notable incident or insight.
Implementation Blueprint You Can Borrow
- Map use cases across your practice: content, research, monitoring, reporting, admin.
- Set principles: disclosure, human-in-the-loop, verification standards and red lines (e.g., no PII uploads).
- Vet tools with IT and legal: data handling, retention, IP terms and security posture.
- Pilot with a small team: define success metrics, risks and QA steps before scaling.
- Create review checklists: facts, sources, tone, brand alignment, regulatory sensitivities.
- Train continuously: ethics, prompts, editing skills and "what to do when unsure."
- Monitor and refine: track errors, near-misses, wins and update policy accordingly.
Ethics, Legal and Oversight
Your reputation rests on accuracy and accountability. Use clear disclosure when appropriate, protect client data, and keep humans accountable for final outputs. Stay current with reputable guidance such as the NIST AI Risk Management Framework and your profession's ethics standards, including the PRSA Code of Ethics.
The Bottom Line
AI works for PR teams when it strengthens human expertise. Keep trust, credibility and measurable outcomes as your north star, and let tools support-never replace-judgment and creativity.
Keep Building Skill
If you're formalizing training for your communications team, explore curated options by job role: AI courses by job. Establishing common standards and shared language accelerates adoption and reduces risk.
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