Stop with the Random Acts of AI
Why buying CoPilot licenses isn't a Strategy
Here is a scenario I see regularly
A leader returns from a conference, terrified they are falling behind (guess what? everyone feels this way, even those on the front lines…like me). The leader issues a mandate: “We need to be an AI-first company.” They buy 500 Enterprise licenses for Microsoft Copilot or ChatGPT. HR sends out a generic usage policy. An AI council forms.
And then... nothing changes.
Oh, sure, a few are using it to write emails or summarize meetings. And when put under the microscope, a few power users step forward. But the fundamental way the business creates value hasn’t shifted. There is no efficiency gain. No innovation. Just a monthly bill for software that sits idle.
I call this Random Acts of AI.
It’s the corporate equivalent of buying a treadmill, putting it in the basement, and wondering why you haven’t lost twenty pounds yet. You bought the tool, but you didn’t build the system.
The Trap of Running AI Pilots
When you lack a systematic approach, you end up in Pilot Purgatory.
This is where your organization runs dozens of “cool” experiments. Marketing tries an image generator. Sales tries a script writer. Engineering plays with code assistants.
They are all successful in isolation. But they never scale. They never connect. They never change the bottom line.
You are treating AI as a tool to be installed, rather than a capability to be managed.
In Hyperadaptive, I outline why the companies that succeed—the ones that actually move the needle—move beyond AI licenses and build an infrastructure to support it.
Building the Machine
AI changes too fast for traditional, top-down training programs. By the time you finish the slide deck, Co-Pilot has updated twice. You need a new way to create AI literacy. I call it an AI Learning Flywheel.
This “always-on” infrastructure does three things:
1. Supports Your Champions (The AI Leads)
In most companies, the “AI Lead” is just an enthusiastic employee doing this off the side of their desk. They are exhausted. They are trying to do their day job and teach the rest of the department how to prompt.
The Fix: You must formalize these roles. Not by adding headcount, but by giving them hours in the week dedicated solely to AI exploration and dissemination. If you don’t give them time, they will burn out, and your AI knowledge will walk out the door with them.
2. Clear Roles for Information Flow
Who is watching the horizon? Who is deciding which tools are safe? Who is teaching the interns? In the Hyperadaptive Model, this is the responsibility of the AI Activation Hub.
The AI Activation Hub owns:
AI updates (e.g., “What does the new Claude update mean for our coding workflow?”).
Turning those updates into specific use cases for your team.
Success patterns and prompt libraries so your team isn’t reinventing the wheel every week.
3. Always-On Infrastructure
AI doesn’t sustain itself. You need:
Dedicated Slack/Teams channels that are hyper-local for AI use cases
Regular “Office Hours” where anyone can ask a dumb question without judgment.
A rhythm of forums that feature internal wins (social proof is powerful).
From Scattered to Systematic
Random Acts of AI feel good in the short term because they look like activity. But activity is not progress.
Real transformation requires the unsexy work of building the plumbing. It means supporting your people, creating hubs for knowledge to flow, and treating AI adoption as a discipline, not a chaotic free-for-all.
If you feel like your AI efforts are scattered, stop buying more licenses. Start building your Hub.
— Melissa
Next Steps
Is your organization stuck in Pilot Purgatory? Discover your strengths and where to put your efforts. Get your custom report here.
Go deeper: In Hyperadaptive, I dedicate a full chapter to designing your AI Activation Hub. Preorder the book.