Want Better AI? Build Teams That Learn Fast.

You don’t need a standalone AI team. You need a system that knows how to learn.

One of the first questions leaders ask when considering AI is:

“Who should own this?”
“Do we need to hire a team?”
“How will this affect the people we already have?”

It’s a fair concern. But the answer isn’t to centralize all things AI into a new silo. It’s to build learning capacity into the teams you already trust.

AI is a capability that touches strategy, operations, technology, and people. And the organizations that get the most value from it aren’t necessarily the ones with the biggest teams or the deepest pockets. They’re the ones that learn the fastest.

Why a dedicated AI team isn’t the full answer

There’s nothing wrong with having focused technical expertise. In fact, an AI lab or center of excellence can be a smart starting point, especially for organizations that need space to experiment, explore use cases, or build foundational knowledge.

But if that work stays siloed – removed from day-to-day operations, disconnected from teams closest to the problem – it’s unlikely to scale in meaningful ways.

Here’s where these efforts often struggle:

• The work is hard to translate into everyday impact
• Operational teams don’t know how (or when) to engage
• Learning and ownership stay bottled up in one part of the organization

The goal isn’t to avoid centralized effort, it’s to ensure it’s not the only effort. A CoE can lead, guide, and coach. But value shows up when teams across the organization are empowered to ask good questions, act on insights, and adapt in real time.

The better question: how do we build learning loops into our teams?

Every AI initiative is an opportunity to get smarter – not just about data, but about how your business works. The teams best positioned to unlock that learning are often cross-functional: blending domain expertise, operational insight, and just enough technical fluency to ask the right questions.

What they don’t need is perfection. What they do need is space to test, reflect, and adjust without fear of failure or finger-pointing.

That’s how AI moves from pilot to capability. Not by scaling tooling, but by scaling trust, feedback, and context across teams.

You don’t need an AI team. You need a learning system.

That system includes:

• Business leaders who ask smart, targeted questions
• Teams that are incentivized to improve—not just execute
• Coaches or partners who can guide and de-risk early efforts
• Space to reflect on what’s working, what isn’t, and why

This approach reduces fear, increases visibility, and avoids AI being perceived as a threat to people’s roles. Instead, it becomes a tool teams are empowered to shape because they helped design how it’s used.