Most AI initiatives don’t fail because of bad models or weak vendors. They fail because people quietly opt out — by ignoring the tools, undermining the effort, or waiting it out. This post teaches you how to prevent that.
Almost every company makes the mistake of thinking that AI adoption is about investing in technology. That’s the easy part. You can make technology do whatever you want. But you can’t make people do whatever you want. In fact, most humans resist change. The focus must be on people, first and foremost.
I have a master’s degree in organizational development and led technology change efforts at a Fortune 100 company for nearly a decade. Here are lessons I learned from the (many) bumps I’ve had along the way.
The big assumption
This post is not about creating a business case for AI. This post is to help you AFTER your leadership team is onboard, the strategy is in place, and the money and resources are approved.
A Wharton study concluded that three-quarters of the businesses were getting a positive return on their AI investments. Businesses typically take decades to successfully deploy new technologies. Progress after just three years is striking. As AI continues to improve and workers become more adept at collaborating with machines, the gains will compound. Over a billion people use generative AI models every month. Not all uses are productive, but many will be.
The key is getting people to use it.
Let’s get those people moving …
1. There’s no such thing as a grassroots AI adoption effort
If you’re trying to enable a profound technological change in your company, it won’t happen just because you want it to. This project must be understood and actively supported by the senior executive who owns the AI adoption strategy and budget.
This is non-negotiable.
Every technology adoption effort comes with frustrations, delays, and problems. You must be able to turn to a high-ranking person for support when the sh*t hits the fan. This is your “air cover.”
In a small company, this sponsor/protector may be the owner. Or, it could be a department head in a large company. But the person at the top must buy in because this is not simply an investment — it’s a cultural change. And only the leader at the top can influence culture.
2. Show active sponsorship
Once your leadership is onboard, they need to show up and let people know this is a critical business effort in three ways:
- Make AI adoption part of annual goals tied to bonuses and compensation.
- Ask questions about progress and adoption in every staff meeting. One business owner asks anyone who comes to him with a problem whether they’ve tried using AI to solve it first. Using AI as a default has now become part of the company culture.
- Repeatedly emphasize why this is important to the business. In my corporate days, we used to have a saying that an executive had to hear something seven times before it sank in.
3. Don’t name it
Don’t make AI adoption a “project” with a name.
If your effort has a name like “AI Future,” it becomes a target for derision. A project with a name makes people think it is a short-term management fantasy that will eventually go away.
When manufacturing locations first introduced electricity to the workplace, they didn’t call it “Operation Lights On.” They just did it because it moved them into the future.
4. Assign an SPA
AI adoption is a team sport.
And like any team sport, progress breaks down when everyone’s chasing the ball, but no one knows their position. But when positions are clear, people stop guessing, and they know how AI fits into their work and how their work fits into the larger system.
Coordination is what turns AI from a collection of half-used, misused, or abandoned projects into something that actually works and makes a difference.
And that requires a manager. Every change management effort must have a single point of accountability (SPA). This is the person who lives and breathes this effort every day. Their career depends on success.
Back when social media was taking off, a common mistake was assigning “Jimmy from the mailroom” to lead the effort because he was the only person on Facebook. Of course, that was a recipe for disaster.
The ideal SPA is somebody who deserves more responsibility, is trusted, and is ready for a new role. They will be motivated to succeed because they know a promotion is likely next.
I find that 90% of the time, a change effort fails because there was no SPA.
5. Acknowledge the fear
Bringing AI into an organization might cause real fear among employees. It could represent
- Job displacement anxiety
- Fear of looking incompetent
- Loss of control or expertise
- Ethical unease that they don’t know how to articulate
Before you label someone as “anti-AI,” ask what they’re protecting. In my experience, resistance is almost always about fear of irrelevance, exposure, or loss of identity.
Don’t try to erase the fear — legitimize it. Be firm about the direction and acknowledge the unknowns: “Some of you are right to be concerned. AI will change roles. Some tasks will disappear. Some skills will matter less.”
This signals honesty, builds trust, and removes the taboo around saying the quiet part out loud.
Once fear is spoken, it loses some of its power.
6. Middle managers are your make-or-break layer
If you’re in a larger company, the middle managers are your key to success. Middle managers:
- Control day-to-day workflows
- Translate strategy into behavior
- Set the emotional tone toward a change effort
- Can quietly kill adoption by deprioritizing it
These are your internal influencers who can either propel or torpedo AI adoption. To keep them on board,
- Train them first
- Give them scripts, not slogans
- Explicitly remove old KPIs that conflict with AI experimentation
- Reward their advocacy and progress
7. Start with the willing
Chances are, there will be people on the team excited about AI and ready to lead. Give them an opportunity to shine.
- Identify early adopters who are already curious/enthusiastic
- Let them pilot and become your internal champions
- Use their success stories to build momentum before expanding to skeptics
- Don’t waste early energy trying to convert the resistant — let peer proof do that work for you
Of course, some people will not get on board, so you must …
8. Address obstinacy immediately
There will be resistance. That’s natural. But when a person is a flat-out obstacle to progress, address it immediately. Actively working against a change effort can become an organizational cancer.
If the resistance isn’t something you can address yourself, defer to the power of your sponsor with something like, “I’m sorry you are anti-AI and against this effort. This is a priority to our boss, who is sponsoring this, so let’s bring it up with her.” (Refer to point one of this post!)
The most effective change effort I’ve ever been part of accelerated to light speed when the CEO fired a vice president who was blocking the change. It was a thunderbolt that said, “Failure is not an option. Get on board.”
9. Create rational metrics
Here is a piece of advice that might seem controversial.
At least for the first year or two, measure adoption instead of ROI. My thinking goes like this:
AI is transformational, like lightbulbs or air conditioning. Is anybody in Dubai trying to measure the ROI of air conditioning? No, because it enables just about every success in that desert country.
If no one adopts AI, you’ll never see an ROI, right?
Potential metrics might include:
-
% of employees who used AI weekly
-
% of workflows with AI touchpoints
-
Self-reported confidence scores over time
-
Number of AI-assisted decisions vs. manual
10. Build in quick wins
In the early days of a change effort, it’s important to create momentum and positive vibes. And nothing does that better than a positive story.
If employees are talking about their AI victories and breakthroughs, quickly record a video and share it with the leadership team. Set modest adoption goals that will spark positive conversations when exceeded.
And most important, when you reach milestones and achievements, don’t sit on them. Communicate, communicate, communicate.
It’s also important to protect early experiments and failures and share “this didn’t work, here’s why” stories. I have a friend at Dell who meets with each sales leader quarterly to report on AI experiments, even if they didn’t work. This builds psychological safety, which is essential for behavior change.
AI adoption isn’t a technology rollout. It’s a leadership test. The companies that win won’t be the ones with the smartest models but the ones that helped their people cross the bridge from fear to fluency. I hope this post helps you think through your success factors.
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