Don't Be That Guy: How Leaders Kill AI Adoption By Trying Too Hard

Don't be the CEO who announces productivity gains before your employees have even figured out how to use the tools.

You know the type. They read about AI in Harvard Business Review, get excited about 30% efficiency improvements, and immediately send a company-wide email about "doing more with less" and announce a hiring freeze.

Then they're shocked—shocked—when AI adoption stalls, employees hide their usage, and the promised productivity gains never materialize.

This is an unforced error. You're turning a capability enhancement into a threat. Don't be that guy.

The AI Dividend Is Real (But You're Handling It Wrong)

When employees figure out how to use AI effectively, they create real value. A sales rep who used to spend hours preparing for client calls now does it in minutes, with better insights. A developer who writes code twice as fast with fewer bugs. A marketing analyst who can prototype ideas that used to require weeks of back-and-forth with IT.

This productivity improvement—let's call it the AI dividend—is real. And it's creating a problem for leaders who don't know how to handle it.

The problem isn't the technology. The problem is leaders who try to capture this dividend before it's even been created.

This Has Happened Before (And We Didn't Screw It Up)

Remember when your company rolled out:

Spreadsheets? Finance people got dramatically more productive. Some became wizards at complex models. Others used them for basic calculations. High performers distinguished themselves and moved up.

Email? Communication timelines collapsed. Some people became masters of clear, efficient written communication. Others... didn't. You didn't need a special "email dividend sharing framework."

CRM systems? Sales productivity transformed. Top performers found ways to use the tools brilliantly. You rewarded them through commissions, promotions, and recognition.

Messaging systems? Team coordination changed overnight. Some teams figured out great workflows. Others struggled. You didn't announce company-wide efficiency targets the day after rollout.

None of these required elaborate frameworks for "sharing the productivity gains." High performers got rewarded through normal channels. Companies benefited naturally from better work. Everyone understood this was how technology adoption works.

So why are we being weird about AI?

The Premature Extraction Problem

Here's what's happening in too many companies right now:

1. Leadership gets excited about AI's potential 2. They read about productivity improvements and cost savings 3. They immediately announce expectations: hiring freezes, headcount reductions, efficiency targets 4. Before anyone has actually figured out how to use the tools effectively

This is like announcing you're cutting support staff the day you install new messaging software, because you read that it "reduces meeting time by 20%."

You're calling your shot before you've even taken it.

And here's what happens next:

- Employees who figure out AI keep it secret (because why would they reveal productivity gains when the company already announced they'll extract them?) - Teams resist adoption (because it feels like a threat, not an enhancement) - Your best people start job hunting (because they can see this is going poorly) - The productivity gains you counted on never materialize - You blame "resistance to change" instead of recognizing you created it

Don't be that guy.

What Good Leadership Actually Looks Like

Imagine your operations team comes to you asking for a new hire, right as you're rolling out AI across the company.

Bad response: "We're not hiring. We just invested in AI and expect everyone to be more productive. Figure it out."

Good response: "We've heard AI can do some amazing things, and we're rolling it out to everyone with real training and support. How about we see what happens over the next few months when your team is up to speed? If you still need someone after that, let's talk."

See the difference?

The first approach creates fear and resentment. The second creates space for capability building while managing expectations reasonably.

Here's what actually works:

1. Provide Real Tools and Training

Not just access to ChatGPT. Actual capability building. What does good AI use look like in your context? How does it apply to your workflows? Budget for this like you would any other technology rollout.

2. Say Explicitly What This Is For

"AI is meant to enhance your capability, not replace you. We expect some people will become great at this and some will be adequate. That's fine—it's like any other skill. High performers will be rewarded through our normal systems."

Say this clearly. Say it repeatedly. Mean it.

3. Don't Announce Productivity Expectations Prematurely

Let gains emerge organically. When they do, recognize them. But don't declare victory before the battle has started.

Your employees aren't stupid. If you announce efficiency targets before they've even been trained, they know exactly what you're doing. And they'll respond accordingly.

4. Let Your Performance Management Systems Work

Some people will become incredibly productive with AI. Others will be competent. A few will struggle.

This is exactly like every other technology adoption. Reward the high performers through promotions, raises, expanded responsibility, and flexibility. Your existing systems work fine for this.

You don't need a special "AI dividend sharing framework." You need to not sabotage the systems you already have.

5. Trust the Gains Will Flow Naturally

When employees get better at their jobs, the company benefits. When developers write better code faster, you ship better products. When sales reps have better customer insights, revenue grows. When operations teams work more efficiently, costs decline.

You don't need to extract these gains through announced policies. They'll flow to the company naturally through better work.

The companies trying to capture the dividend explicitly are the ones ensuring they never see it.

Don't Be That Guy

AI isn't everywhere in the productivity data yet. Maybe it will be eventually. Maybe the hype is real. Maybe it isn't.

But here's what we know for certain: The companies that benefit most from AI won't be the ones trying hardest to capture explicit productivity gains. They'll be the ones treating it like any other capability-enhancing technology—investing in tools and training, making it clear it's for enhancement not replacement, and trusting their performance systems to work.

The ones announcing efficiency targets and hiring freezes before anyone's even been trained? They're guaranteeing their best people will either hide their AI usage or leave for companies that aren't being weird about this.

The AI dividend is real. But you can't capture it by announcing you're going to capture it. You can't realize productivity gains by declaring them in advance.

The harder you try to grab the AI dividend, the more certainly you'll never see it.

So provide great tools, real training, and clear messaging. Then get out of the way and let your systems work. The gains will come, and they'll benefit everyone.

Just don't be that guy who kills adoption before it starts.