RTI International’s step-by-step approach.
RTI International recruited a test group of employee volunteers before widely adopting AI.
That group eventually named itself the Gen AI Impact Team. It included employees from different career stages, tenures and comfort levels with technology. Some were naturally curious while others were hesitant about AI and wanted to understand it better. Part of the team worked in internal communications while others handled more public-facing or scientific content.
“It wasn’t our most technologically savvy folks,” said Kami Spangenberg, VP of corporate communications at RTI International. She will be speaking at PR Daily Conference next month. “It really was a group of team members who said, ‘I’d like to learn about that.’”
Spangenberg said inclusivity was intentional because different types of employees would spot different opportunities and risks. This is something all organizations could benefit from, she said.
“There could be someone who is incredibly curious,” she said. “Or it could actually be someone who is maybe a little trepidatious and a little fearful, but what they want to do is dive into it in order to make it less intimidating.”
- Give employees room to explore
Once the team formed, RTI let them experiment over a two-month period.
Spangenberg’s team provided limited funding so the group could test paid versions of AI tools when needed. Beyond that, the team was largely self-directed, she said.
“I really gave them freedom to go out and evaluate and test different tools,” she said.
They evaluated tools for drafting internal content, conducting research and supporting more technical communications work tied to RTI’s scientific mission.
Spangenberg asked the group to return with a short report documenting:
- Which tools they tested
- How they tested them
- What kinds of work they used the tools for
- Which platforms seemed most useful
- What workflows showed promise
“It was not for them to come back and give us strict recommendations,” she said. “It really was, ‘Here’s what we learned.’”
Rather than thinking of AI adoption like a one-time rollout, RTI looked at it as an ongoing and evolving learning process, she said.
“I really did set my mind to: we’re on a journey,” Spangenberg said. “It doesn’t necessarily have a final destination at this time.”
- Identify what actually works
The team identified which tools worked best for specific tasks. Some were better suited for internal drafting. Others helped with research or more technical scientific content, she said. “We had some clarity right away,” Spangenberg said. “It was like, ‘these are the tools that we think we could move forward with.’” That served as an early win, which helped give the team momentum.
The group also started identifying workflows that best matched the tools’ functions.
Then RTI moved into the next phase.
- Expand the pilot across the team
After the first round of testing, the original team extended the test into a broader pilot program across different departments.
They recruited more employees and matched specific AI tools to specific types of work, Spangenberg said.
For example, employees focused on staff communications were paired with tools the Impact team believed would help internal messaging workflows.
“It was guided. They said, ‘we’re going to give you a tool, and we’re going to give you some things that we think it could help you with,’” Spangenberg said.
Employees tested the tools during their regular work and reported back using feedback forms. They documented whether the AI actually helped, where it struggled and what they would change.
What they found was that the feedback really helped avoid a common AI rollout problem, which is overwhelming employees with too many disconnected tools and unclear expectations, Spangenberg said.
“It shouldn’t feel like a giant wave crashing over someone and you don’t quite know what to do with it,” she said.
- Share the results
The Impact team gathered feedback from across the departments, identified patterns and shared what worked back with the larger group.
“You swap the tips and tricks, and you start learning from others,” Spangenberg said. “Then I think it gets momentum in the team.”
Matching tools to real workflows helped employees discover where AI was actually useful inside their own jobs, and in turn, helped the company form a broader AI structure and governance.
“It’s all about relevance,” she said. “Does this tool that we all have now actually help me do what I need to do?”
Spangenberg said comms leaders have a responsibility to help teams navigate AI thoughtfully rather than thinking of it as either a silver bullet or a threat.
“AI is a change,” she said. “It’s something that we need to figure out how to adapt into our work in a responsible way. With the right approach, with humans at the center, it can help you move in a way that can create more efficiencies.”
Courtney Blackann is a communications reporter. Connect with her on LinkedIn or email her at courtneyb@ragan.com.
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