The Infrastructure Gap: Why Your AI Isn’t Scaling

(And a few thoughts on what to do about it)

Remember When We Rolled Out PCs?

Remember the early 1990s? When the Personal Computer revolution hit the enterprise, we didn’t just drop a beige box on every desk, pat the employee on the shoulder, and wish them “good luck.”

We built an entire world to support that shift. We built IT departments. We hired Help Desk technicians. We trained installers and troubleshooters. We instinctively knew that the hardware was useless without a human support layer to ensure it actually worked.

Yet, as I look around at how organizations are handling the AI revolution (a shift arguably bigger than the PC) I see us making a catastrophic error. We are buying the licenses, but we are forgetting to build the infrastructure.

I know you’re feeling this. I speak with executives every week who are trying to find direction amidst the noise. You’ve purchased Copilot or ChatGPT Enterprise. You’ve run the ‘Introduction to GenAI’ sessions. You have a few eager beavers leaning in, but it isn’t getting traction at the scale you want. It’s not repeatable. It’s not scalable.

Your Board is asking for ROI, and you are staring at a workforce that is largely paralyzed.

We Need Key Support Systems

The problem isn’t the technology. The problem is that you are trying to implement AI without the plumbing. You are expecting “AI flow” without building the pipes to carry it. You need a robust support infrastructure to Spark usage, Spread best practices, Scale it across the company, and Sustain it as the models change.

In my work on the Hyperadaptive Model, I’ve found one critical piece missing in almost every stalled organization: The AI Activation Hub.

Think of this as a self-sustaining network of AI CoEs that super-charge the organization.

Your network of Activation Hubs serve as the “axles” of your learning flywheel. They are a living distribution channel for expertise, training, and support. Just as we needed IT support for the PC, you need specific support structures for AI right now:

• Triage and Troubleshooting: When one of your people gets stuck in a hallucination loop, who do they call? Your Hub provides virtual office hours. It normalizes the messiness of learning so your people don’t hide their mistakes.

• Translation (Support for AI Leads): You cannot rely on a central IT team to teach Marketing how to write campaign briefs with Claude. You need embedded champions (I call them AI Leads) within the departments. But these leads are tired. The Hub exists to support them, providing the resources they need so they don’t burn out.

• Dynamic Knowledge Management: That static training video you paid for? It still references ChatGPT 2.0. The Hub manages an AI Knowledge Engine, a living system that captures the brilliant prompt your engineer wrote yesterday and redistributes it to the rest of the team today.

Final Thoughts

If you are looking at your dashboards and seeing low adoption, stop. Stop buying more tools. Stop scheduling more generic, static training.

Start building the missing layer. Establish one or more AI Activation Hubs. Identify your internal AI Leads and give them the time—real, protected time—to support their peers.

You wouldn’t expect your house to have running water without pipes. Don’t expect your organization to have AI capabilities without the infrastructure to support them.

Until next time,

—Melissa

Pique your interest?

The AI Activation Hub is just one part of the AI Learning Flywheel. Learn more here.