The Most Important AI Role Has Nothing To Do With Code

When organizations think about AI transformation, they immediately focus on technical roles: data scientists, developers, prompt engineers. But what if the most important AI role in your organization requires zero technical expertise?

This isn't a provocative question for the sake of being provocative. It's a genuine insight from watching dozens of organizations struggle and succeed with AI adoption. Because here's what most miss: This isn't a technology adoption curve. It's a human transformation curve. And the people who catalyze that transformation often aren't the technical experts.

If your organization is betting big on AI engineers while ignoring community builders, you might as well light your transformation budget on fire. I watched a Fortune 500 company spend millions on AI talent only to see adoption stall in the low teens %. Meanwhile, a government agency with a tiny fraction of that budget achieved organization-wide transformation mostly through the efforts of a single individual passionate enough to organize monthly Zoom calls.

You Already Know Half This Story

One of my most-beloved recent posts describes how a Facility Manager at the National Park Service—with no technical background whatsoever—built an AI tool in 45 minutes that's saving thousands of days of labor across the park system.

Adam, the facility manager, created a simple tool that automated the creation of complex funding request documents. The impact was staggering: what used to take days now took minutes. His colleagues started sharing the tool, and soon facility managers across the country were using it.

People loved this story because it showed that AI impact doesn't require a computer science degree or coding expertise. Just curiosity, a clear problem, and 45 minutes.

But here's what I didn't tell you in that post: Adam's breakthrough wasn't spontaneous. It was the direct result of someone working upstream.

Meet the Person Upstream of Innovation

Want to identify the Adams in your organization and unlock opportunities like the one he found? You need to look farther upstream to a role I've rarely seen discussed: the Convener.

At the National Park Service, that person is Cheryl Eckhart. While many organizations are busy chasing the shiny new AI tools, Cheryl was doing something far more radical: creating a space where people could actually use them. Months before Adam built his tool, she had taken the initiative to start convening a community of practice around AI. With no technical background herself, she understood something more fundamental: people need spaces to learn, experiment, and share.

Cheryl signs every email with "Today is a great day for learning"—a philosophy that defines her approach. She's not an AI expert; she's a catalyst who creates the conditions for others to become AI experts.

What does this look like in practice?

1. She hosts monthly virtual "office hours" where AI enthusiasts, skeptics, and the curious can gather

2. She maintains an active Teams channel where people share resources and custom GPTs

3. She ensures that each meeting spotlights someone new sharing what they've built

4. She curates the best examples and actively promotes them across the organization

Without Cheryl creating this ecosystem of learning and sharing, Adam's tool would have remained just another isolated innovation, rather than a system-wide transformation.

The Exponential Impact of Conveners

Just last week, Cheryl's community spotlighted another breakthrough: a Park Service employee who created a GPT that helps colleagues reformulate their work accomplishments as "impact bullets" for the Department of Government Efficiency (DOGE).

The tool was inspired by—and trained on—Elon Musk's publicly available writing to help translate government-speak into language DOGE would appreciate. Created just weeks ago, it's already been used thousands of times.

This is how exponential innovation spreads: not through top-down mandates but through communities of practice where people feel safe to experiment, share, and learn together.

As I've written before, if you want to Catalyze AI Success in your organization, you need to create dedicated capacity to realize ideas. Cheryl is that dedicated capacity—not because she's building the tools herself, but because she's creating the environment where others can.

The Convener's Toolkit

The irony is delicious: As some organizations throw millions at technical AI expertise, true competitive advantage might lie with the person passionate enough to organize monthly Zoom calls.

This pattern extends beyond government. Christa Stout, Chief Strategy and Innovation Officer of the Portland Trail Blazers, hosts what she calls "lunch and launch" initiatives where she helps different teams identify AI opportunities and connects them to resources to realize those possibilities.

What makes conveners like Cheryl and Christa so effective?

1. Regular Forums: Whether weekly, monthly, or quarterly, consistency matters more than frequency

2. Persistent Channels: Slack, Teams, or even email groups where ideas can be shared between meetings

3. New Voices: Actively recruiting different perspectives and showcasing diverse success stories

4. Curation: Not just collecting but actively promoting the most valuable examples

5. Connection: Matching problems with problem-solvers and resources with needs

Note that none of these require technical expertise—just the ability to bring people together and create psychological safety for learning and sharing.

Practice and Community

I've long maintained that a community of practice is one of the most underrated tools in the innovator’s toolkit (aside: the AI Junto’s monthly meetup is one of my few can’t-miss calendar appointments). When people learn together, they accelerate each other's growth. They share shortcuts, troubleshoot problems, and inspire new possibilities.

This is especially true with AI, where the landscape is changing weekly and no one person can keep up with everything. Communities of practice distribute that cognitive load and create collective intelligence greater than any individual could achieve.

As Stephen Kosslyn might put it, conveners help us "think upstream" about innovation. Rather than focusing only on individual tools or use cases, they create the conditions where those tools and use cases naturally emerge and spread.

Your Next Move

If you're looking to contribute to your organization's AI transformation but don't have technical expertise, consider becoming a convener. Here's how to start:

1. Schedule a recurring monthly meeting called "AI Show and Tell" or "AI Office Hours"

2. Create a dedicated channel in your company's communication platform

3. Invite 2-3 colleagues who've already been experimenting with AI to share what they've learned

4. Ask pointed questions that help others see how they might apply similar approaches

5. Curate and broadcast the best examples you find

For your first meeting, here's a ready-to-use agenda:

• 10 min: Welcome and vision for the community

• 15 min: Featured use case presentation from a volunteer

• 20 min: Q&A and discussion about the use case

• 15 min: Brainstorm next areas to explore

You don't need to be the expert. You just need to create the space where expertise can develop and spread.

Because in five years, organizations won't be distinguished by who had the most advanced AI tools. They'll be distinguished by who created the most effective communities of practice around those tools.

And that could be you—after all, today is a great day for learning.

Related: The 45 Minutes That Saved 20 Years
Related: Stop Measuring AI Usage (Start Measuring AI Impact)
Related: Catalyze AI Success
Related: Practice and Community
Related: Beyond the Prompt: Stephen Kosslyn

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