Article
July 30, 2025
By Zack Kavanaugh
When it comes to the success of AI rollouts and adoption, there’s a notable delta between the perspectives of a company’s leaders and its employees.
About a quarter of leaders say their AI rollout has been effective. Only 11% of employees agree.
That’s not just a signal that implementation is lagging – it’s a signal that alignment is lacking. And that gap likely isn’t due to tech – at least not tech alone. More likely, it’s about trust, clarity, consistency, relevance … even identity.
You can launch the right tool with a solid rollout plan behind it. But if employees don’t understand why it matters – or where they fit in – behavior change stalls before it has the chance to take root.
Why Behavior Change Stalls: The Distance Between Intention and Action
Behavior change doesn’t just happen because a tool is available – it has to be intentionally built into the experience. Early. Clearly. With a level of resourcing and support commensurate with what the company has invested in the platform itself.
That means embedding behavior-shaping touchpoints from day one – not waiting for adoption to happen organically. What does this look like in action? Continuous feedback loops to surface and address employee hesitations, leaders modeling new behaviors in visible ways, regular moments of reflection woven into team rhythms, and dedicated roles focused on coaching and practical support – among other things.
People pull back when things feel vague. When the shift doesn’t connect to what they care about, or how they see their role. Even the best tools get overlooked if the environment around them doesn’t support the change they’re meant to create.
Where Behavior Change Breaks Down: The Subtle Signs of Resistance
But where exactly does the friction show up?
Resistance doesn’t always show up as vocal opposition – more often, it shows up in silence. A tool gets rolled out, but questions go unasked. Team conversations sidestep it. Some employees disengage or quietly revert to old habits like manually analyzing large swaths of data or generating meeting summaries and first drafts from scratch.
This refusal isn’t manifested as loud rebellion. It’s slow fade. And in AI transformation, that quiet drift is one of the biggest threats to sustained impact.
Left unchecked, that disengagement can erode tool ROI – dragging down productivity, creating adoption gaps across teams and limiting the career growth of those who hesitate, especially in roles where fluency with AI is quickly becoming table stakes. In short, when employees don’t buy in, the business can’t move forward at the pace it needs to.
The good news? These signals are visible – if you know where to look. Spotting and addressing them early can protect your investment, align your people and accelerate progress where it matters most.
The Three Layers of Hesitation: Enterprise, Team and Individual
For companies struggling to drive AI adoption, this is the moment to step back and start asking simple questions like the ones here.
While the tools will get better and the use cases will expand, none of that guarantees impactful adoption.
Right now, most organizations don’t need a newer generation of the technology. They need better feedback loops. More storytelling and open conversation. A stronger bridge between AI strategy and lived experience.
And more honest signals from leaders – that this isn’t just about the next tool, it’s about how the work is changing, why that matters and how the organization is committed to making space for people to come along with it.
The Final Takeaway: Change Sticks When Conditions Are Right
Adoption doesn’t accelerate just because the tools get better. And AI doesn’t scale well in confusion. These things happen only when the environment is ready – when culture, clarity and context catch up to the ambition.
That’s when change starts to feel real. And when people decide it’s worth leaning in.
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