Is There an AI Gap Growing Inside Your Marketing Team?

Most marketing leaders will tell you that their team uses AI. But there is a difference between a team that uses AI and a team that improves together and shares its progress.

Often times, there are a few people on the team who have really figured out how to work with AI effectively. They created smarter prompts, developed better workflows, and learned how to feed tools the right context to get consistently useful output. They move faster. But almost none of what they learned passed on to anyone else on the team.

The distance between the two groups can continue to grow if there is no system to close it.

Paul Reutzer put it clearly Episode 221 of the Artificial Intelligence program: In a team of 100 people with access to AI, there are typically five to ten power users who achieve daily milestones. Then there’s everyone. The problem is not the technology. Learning is not treated as a team asset.

What to do about it now

Some places to start:

Find your power users and make their workflow visible. Identify people who consistently impress you with AI, who get things done faster, and who seem to get the most out of the tools. Ask them to document what they actually do. Not a polished tutorial. Just a working description of how they organize their claims, the context in which they are fed, and what they have learned about what works.

Create directed libraries and joint projects. If one person builds a well-organized AI project to write email campaigns that consistently produces brand-relevant output, that project should be accessible to the entire team, not in his or her personal account. Shared resources like these are a practical way to transfer the benefits of one person’s learning to everyone.

Create a light feedback loop. A simple, frequent practice – even fifteen minutes in a team meeting – where someone shares one AI workflow win or experience that week changes the dynamic. It suggests that this kind of learning has value, highlights things that would otherwise remain buried, and gives people specific things to try rather than vague encouragement to use AI more.

Dealing with context building as a group project. The brand guidelines, audience personas, messaging frameworks, and campaign lessons that make AI outputs truly useful are the team’s assets. Its centralization — and ease of loading into AI tools — multiplies the value of everyone on the team using it.

Compound problem

People who are already ahead continue to improve faster. Why? Because they use AI more and learn more from each use. People who do not join this learning cycle almost stay where they are.

Over time, the difference grows. Marketing leaders who get ahead of this now — by building platforms to share learning and capture context — are preparing their teams to build and advance together.

This blog is based on insights from Episode 221 of Artificial Intelligence Exhibition, Hosted by Paul Reutzer and Mike Cabot.

Want to learn more about applying AI orchestration and AI agents to your workflow? Join us at our free virtual site Summit for B2B Marketers On June 25, 2026.