Your employees are already using AI. Just not yours.
Last month, a VP of Engineering posted this to Reddit:
"Last quarter I rolled out Microsoft Copilot to 4,000 employees. $30 per seat per month. $1.4 million annually. Three months later I checked the usage reports. 47 people had opened it. 12 had used it more than once."
The post got 1,100 upvotes. Not because it was unusual — because it was relatable.
The Shadow AI Problem Nobody Talks About
While that VP was getting 47 active Copilot users out of 4,000, something else was happening: engineers on the same team were using ChatGPT and Claude to write code, review PRs, and draft documentation.
They just weren't using the approved tool.
This is shadow AI — unsanctioned AI use that happens because the approved tool wasn't introduced well enough to become habit.
You paid for Copilot. Your engineers are using a competitor's product instead. And you have no visibility into either.
Why This Happens
From the same Reddit thread, the top comment (5,600 upvotes):
"I don't think they convinced anyone what the use cases are for Copilot. Most people don't ask many questions when using their computer — they just click icons, read, and scroll."
That's the diagnosis. Employees weren't given a reason to change behavior. They got an IT email and a recorded webinar. That's not training. That's notification.
The default behavior — click icons, read, scroll — doesn't change unless someone shows you exactly which tasks to do differently and why the AI version is better for those specific tasks.
The Measurement Gap
Here's what makes the 47-of-4,000 problem hard to solve: most companies didn't measure before rollout.
They don't know:
- How long engineers spent on PR reviews before Copilot
- How much time went into first-draft documentation
- What the baseline was for code generation tasks
So when Finance asks "is this working?" — there's nothing to compare against. The ROI question becomes unanswerable.
Only 18% of companies in our benchmark data established a utilization baseline before rollout. The other 82% are flying blind.
The Fix Is Not Complicated
The companies that hit 65%+ utilization within 30 days do three things differently:
1. They pick one workflow. Not "use it for everything" — one specific, high-frequency task where the time savings are obvious. For developers, pre-PR review is usually the winner. For ops teams, it's meeting summaries. Pick one, make it the entry point.
2. They train by role, not by tool. Generic "here's how Copilot works" demos don't stick. Role-specific sessions that answer "what does this replace in your actual workday?" do.
3. They share wins visibly. The teams that sustain usage post weekly: "here's a prompt that saved someone 30 minutes." Isolated wins don't compound. Public wins create culture.
On Shadow AI Specifically
If your engineers are using ChatGPT instead of your approved tool, don't clamp down — understand why.
Nine times out of ten, it's one of these:
- The approved tool wasn't introduced with a clear use case
- The approved tool's output for their workflow was worse on first try (often because prompting wasn't taught)
- ChatGPT was there first and built the habit
The answer isn't restriction. It's a better introduction to the approved tool — one that's fast, role-specific, and demonstrates a win in the first session.
What This Actually Costs
Back-of-envelope for a 100-person engineering team:
- Copilot licenses: $30/seat × 100 = $3,000/month
- At 47/4,000 utilization (1.2%): you're getting value from $36/month of that spend
- At 65% utilization with training: value from $1,950/month
That's a $1,914/month gap. A one-time training investment closes it permanently.
We built a free calculator that lets you run this math for your actual team size: 👉 askpatrick.co/roi-calculator.html
Ask Patrick helps engineering teams close the gap between "we deployed this tool" and "everyone actually uses it." Flat-fee co-work sessions, no per-seat pricing. askpatrick.co
Top comments (0)