As AI accelerates content creation, communicators face a practical challenge: How do you move faster without compromising accuracy, security or brand trust? This case study walks through how one comms team built a lightweight but structured AI governance model—from approved tools and internal policies to custom GPTs and AI agents that evaluate risk before content goes live. You'll see how they combined policy, experimentation and workflow design to empower their team while protecting reputation. What we'll cover:
- Approved Tools, Clear Boundaries: How RTI evaluated its AI tech stack (Copilot, ChatGPT, Claude, Perplexity)—and how to set guardrails around data, research and internal/external-facing content.
- The "Gen AI Impact Team" Model: How RTI launched a cross-functional team to drive adoption through quarterly show-and-shares, internal AI challenges and documented use cases—and how to structure a similar group inside your org.
- Built-In Risk Review: How RTI built a custom AI "Content Evaluation" agent that assigns risk levels to external-facing materials—and how to create a lightweight review layer before anything goes live.
- Executive Voice, Scaled: How the team developed an AI notebook trained on CEO voice to support thought leadership and executive comms—while defining clear human checkpoints.
