Why Old Habits Block AI Adoption
And Why You Should Create New Habits
I was sitting in a client workshop recently, watching the energy in the room shift. The CIO had just unveiled a sleek new AI rollout: Copilot dashboards, automation pilots, all the right buzzwords. For about ten minutes, the room buzzed with curiosity. Heads nodded. People leaned in. Then someone asked a simple question: “So… do we still have to send our weekly status reports the same way?”
Silence. Followed by a collective sigh.
And just like that, the excitement drained out of the room. Not because the technology wasn’t powerful, but because everyone realized what was coming: the same old routines, just with a shinier tool layered on top. The same endless inbox checks. The same bloated meeting calendars. The same reporting structures that nobody questions.
That moment crystallized something I’ve seen over and over. The hardest part of AI adoption isn’t the tool itself. It isn’t the training. It isn’t even the price tag.
It’s habits.
The deeply ingrained, automatic behaviors that make us feel safe, even when they’re outdated. And until we deal with those, AI will never deliver the transformation leaders are hoping for.
Why the Brain Clings to the Familiar
Neuroscience has a simple explanation for this: your brain is lazy in the best way. It likes efficiency. And the most efficient path is always the one it has taken before.
That’s why when you open Outlook, your hand almost automatically hovers toward your inbox. Even if you promised yourself you’d start the day with deep work. Even if you know your inbox is a trap.
This is the habit loop at work:
Cue: The red badge, the ping, the thought of “what if something urgent is waiting?”
Routine: You check.
Reward: A hit of dopamine from clearing one message… followed by the weight of 37 more.
The loop doesn’t care whether the outcome is good or bad. It only cares that it’s predictable. Predictability equals safety.
When leaders introduce AI into this loop without changing the underlying habits, nothing shifts. People still open their inbox first thing. They still schedule unnecessary meetings. They still default to the same approval chains. AI becomes a coat of paint on an old house. And then they wonder why the foundation still creaks.
Why Systems Beat Willpower
Here’s the uncomfortable truth: you can’t “will” people into new habits. That’s where systems thinking comes in. A system is just a set of reinforcing loops. If those loops reward the old way of working, the new tool, no matter how powerful, will never stick.
If performance reviews still reward busyness, people won’t use AI to shorten meetings. If leaders still demand status reports in the same format, no one will let Copilot generate them differently. If approvals are tied to hierarchy, AI recommendations will sit idle, waiting on human bottlenecks. The system rewards the familiar, so the familiar wins.
When I was at Microsoft, I saw this play out repeatedly. Teams would roll out Copilot with great enthusiasm. People got excited during training. They could see the potential. But a few weeks later, usage flatlined. Why? Because the system didn’t change. They were still operating under the same expectations, the same processes, the same reporting chains. AI was present. Habits were stronger.
If you don’t change the system, the old loops quietly pull people back to safety. That’s why transformation stalls, not because the technology failed, but because the environment kept rewarding yesterday’s behaviors.
Back to First Principles
When in doubt, go back to first principles and strip everything down to its essence.
Ask:
What is the actual job we’re trying to get done?
What is the simplest path from input to outcome?
Where are humans truly needed, and where are they just placeholders for comfort?
When you do this, you stop layering AI on top of broken systems and start designing new ones where AI fits naturally. For example, instead of asking AI to summarize meeting notes, ask why you’re holding that meeting in the first place. If the real goal is alignment, maybe a Copilot-generated briefing replaces the meeting altogether.
First principles thinking cuts away the noise. It helps rebuild your workflow from the ground up, where human effort, AI capability, and business value align. Once that happens, adoption stops being a struggle. It becomes a natural next step.
Rewiring Habits with AI
If you want AI adoption to stick, you have to pair technology rollout with habit rewiring. It’s not just about teaching people to click buttons but more about helping them form new loops. Start by picking one loop to disrupt. Don’t try to fix everything at once. Choose a single behavior that drains energy or blocks change, like checking email first thing in the morning.
Then insert AI into the routine. Instead of opening your inbox raw, start by asking Copilot: “Summarize my top ten urgent items. Prioritize by deadlines and relevance.” You’ve just introduced a new cue, a new routine, and a new reward. Next, reinforce it through systems. Leaders should ask for AI-prioritized updates, not manual ones. That signal alone reinforces the new behavior.
And finally, celebrate the win. The brain needs closure and reward, a shorter meeting, a cleaner inbox, or a few minutes reclaimed all count. Recognition, even small, cements the loop. This is how new behaviors take hold, not through dashboards or KPIs, but through rewiring the tiny loops that govern how we actually work.
The Psychology of Safety and Change
When I talk to executives about why their teams resist AI, I remind them: it’s not usually a skills gap, it’s a safety gap. Habits create a sense of control. When people have followed the same routines for years, those routines become a psychological anchor. They’re the proof that “I know how to do my job.” AI threatens that proof, not because it replaces them, but because it challenges the comfort of knowing.
That’s why leaders who focus only on training miss the bigger opportunity. You can teach people how to use AI in a day. But helping them feel safe using it? That’s leadership work. When you address the emotional side of change, when you connect new habits to meaning, confidence, and autonomy, you transform resistance into curiosity.
From Compliance to Curiosity
Adoption doesn’t happen because people are told to use a tool. It happens because they want to explore what’s possible with it. One of the most effective leaders I’ve coached approached AI adoption like a scientist. She encouraged her team to run experiments: “Try one workflow this week. Share what surprised you.” That simple shift from “use this tool” to “try this experiment” turned compliance into curiosity.
Within a month, her team wasn’t just using Copilot; they were improving their own workflows. They built an internal AI playbook, shared prompts, and found ways to automate painful tasks leadership hadn’t even identified. The difference wasn’t the tool but their mindset. Curiosity scales faster than compliance.
Where Real Transformation Begins
The next time you sense resistance in your team, don’t ask, “Why aren’t they using AI?” Ask, “What habit is this threatening?” That’s where transformation really begins.
AI doesn’t fail because of missing features or lack of training but rather through resistance of holding on to old habit loops that never got rewritten. Rewire the loops, and the technology will follow.
If this resonated, stay close. Each week I share reflections on how to not just adopt AI, but reshape the way work happens, one system, one habit, one loop at a time.
Rewiring habits,
Yen Anderson