I've noticed something interesting about the current AI GTM landscape.
Most AI companies seem to be selling to the same customers.
Other AI companies.
Tech startups.
Large enterprises.
The companies that already have clean data, clear processes, and teams that know how to adopt new software.
And honestly, it makes sense.
Those customers are easier.
Their CRM is already set up.
Their workflows are documented.
Their data lives somewhere accessible.
You can plug into existing systems and start showing value quickly.
But it makes me wonder if we're all looking in the same place.
Because when I think back to my operations experience, most businesses don't look like that.
Not even close.
We talk about AI as if everyone is using it.
Most people aren't.
Or if they are, they're using it in isolated ways that never become part of the business.
The spreadsheet lives on someone's desktop.
The process exists in one employee's head.
Customer information is spread across five different systems.
Half the work still happens over phone calls and text messages.
The irony is that these businesses might benefit from AI the most.
A 5% improvement at a highly optimized company is nice.
A 50% improvement at a messy company can completely change the business.
The problem is that software alone doesn't solve the problem.
Someone has to help them get there.
The challenge isn't the AI.
The challenge is the implementation.
Someone has to untangle the process.
Organize the data.
Understand how work actually gets done.
And walk alongside the customer until the system becomes part of the business.
That's hard to scale.
Which is probably why most startups avoid it.
But I keep wondering whether that's exactly where the opportunity is.
Not in selling AI to the companies that are already AI-native.
But in helping traditional businesses cross the gap.
The more people I talk to, the more I think the bottleneck to AI adoption isn't model quality.
It's organizational readiness.
And those are very different problems.