How to Build a Culture of AI Fluency: Marketer Learning at the Speed of Change
The pace of AI innovation isn’t just fast—it’s energizing. For modern marketing teams, it presents a rare opportunity: to create new value, reimagine workflows, and unlock creative potential. But that opportunity hinges on one key ingredient: AI fluency.
According to Forrester’s Predictions 2025: The Future of Work, only 14% of global individual contributors score high on AIQ—a measure of understanding, skills, and ethical awareness in AI. This insight brings into focus that the key to aligning business for the age of AI is not about the tech. It’s about building skills, process and capability.
AI fluency—not just access to AI tools—will differentiate top marketing teams.
Here’s the good news: AI fluency is mainly about fostering learners. People who are curious, courageous, and empowered to experiment together.
I’ve come to this realization after a mix of learning and on-the-job experimentation. A few years ago I completed MIT’s “Business Strategy for AI” program, which was an excellent big picture view that leaned towards executive-level planning and justifying AI initiatives. Just this past month, I’ve been a part of multiple MarketingProfs AI workshops, which offered great prompt sequences to reinvent day-to-day workflows. The most valuable takeaways didn’t come from the theory—they came from watching how fast teams could build momentum when we made learning visible, shared, connection-building and exciting.
AI Fluency Is a Team Sport
AI fluency is a collective capability. It’s the ability - as individual or team - to evaluate, test, and apply AI in your context, with a shared sense of purpose and ethical responsibility.
It shows up differently across teams. Some use it to move faster and more efficient. Some to go deeper. Some to explore ideas they didn’t have the time or bandwidth to pursue before.
Marketing teams I work with have tested AI for persona usage, strategy explorations, ideation, outlining, drafting, work reviews, data analysis, sales enablement, objection handling, and much more. The best outputs come when people guide AI through the same step-by-step processes they use for their own work, infusing feedback, human perspective and collaboration.
Build an AI Learning Culture.
The organizations seeing the most progress are creating environments where people feel safe to try, share, and grow every day. Here’s what that looks like in practice:
Psychological safety starts with permission to explore. On my team, we talk weekly about what we’ve tried with AI—good, bad, and everything in between. The more open the conversation, the more connections and curiosity we build.
Leadership modeling is key. When leaders experiment in public, it gives others permission to do the same. During cross-team meetings I've spotlighted AI use cases on data analysis, outlining presentations, ideation, and aligning work to strategy. The energy and engagement has been real.
Feedback loops keep the culture and workflows evolving. We kick the tires by regularly asking: What’s working? What’s worth revisiting? Does this meet our standards? What’s ready to scale?
4 Ways to Build AI Fluency Into the Flow of Work
Building into lightweight, repeatable habits leads to a groundswell of "aha" moments and collective momentum:
AI Office Hours: Open forums to share wins, fails, and learnings. Invite teams to demo how they’re applying AI in context.
Prompt Playbooks: A shared doc of best prompts for real workflows.
Monthly "Try Something" Challenges: Encourage small experiments that teams report back on.
Learning Drops: Share bite-sized insights in Slack or Teams threads.
Normalize Experimentation and Learning in Public
Responsible experimentation is how teams discover what really works—and what doesn’t. Creating clarity on where it’s safe to explore AI—like in internal drafts, non-customer-facing content, or sandboxed environments—helps reduce fear. Quick retrospectives encourage teams to reflect on what they tried, what they learned, and what they’d do differently. And celebrating the logic, effort, and creativity behind the process—not just the outcomes—builds confidence and momentum.
Leadership Sets the Tone
Leaders don’t need to have all the answers, but they do need to set the tone for curiosity. That starts by asking, “What are we experimenting with this month?” It means sharing what you’re learning and trying, even if it’s still in progress. And most importantly, it means creating an environment where people who raise their hand to explore feel empowered, supported, and encouraged to keep pushing the edges.
The Business Upside of Continuous Learning
According to IDC’s Future of Work 2025 Predictions, organizations that foster continuous learning outperform their peers by up to 68%. And their 2024 Human Capital Management Survey showed a 35% lead in revenue improvements among companies that invest in learning-as-a-system.
Why? Teams who learn fast, adapt fast. And companies who invest in people successfully attract and retain talent.
A learning culture helps you:
Build more resilient, adaptable teams
Create an environment that top talent wants to be part of.
Retain top performers in fast-moving markets
Make AI Learning a Living, Breathing Practice
AI’s evolution is dynamic. So should your team’s relationship with it. You don’t need to master every new model or advanced application. You just need to build the muscles to learn, together. Start with: a shared experiment, a prompt library, a team conversation.
Progress beats perfection. Curiosity scales. And the teams who treat learning like a practice and culture will always move faster than the ones chasing the next tool.
Originally published on my LinkedIn newsletter, “Marketing Growth Conversations”, subscribe here.
