Why Great AI Tools Get Rejected by Good Teams
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Why Great AI Tools Get Rejected by Good Teams
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Shane Harris, Director of Harris & Wood, gave his team powerful AI tools.
The reaction was immediate.
“They don’t work.”
“They’re not accurate.”
“This isn’t how we do things.”
From the outside, it looked like a familiar pattern.
Good team.
Good tools.
Poor result.
So the assumption is obvious: Something must be wrong with the AI.
But when Shane looked closer, that wasn’t what he found.
In this episode, we unpack what actually happened inside the business:
What we believed would happen when AI was introduced
What actually happened when the team started using it
What broke in the process
What Shane changed
And why that shift led to over £50,000 of new business in just over 30 days
The tools didn’t change.
The team didn’t change.
The way the business worked around the tools did.
This is the part most agencies are missing.
AI doesn’t fail quietly.
It exposes how your business currently operates.
And when teams expect certainty from systems designed to operate on probability, rejection is almost guaranteed.
If your team is resisting AI…
If the tools feel inconsistent…
If adoption feels harder than it should…
This episode explains why that’s happening—and what it really means.