Nobody Wakes Up Wanting AI
Most AI companies lead with the technology. That's the wrong direction. Businesses don't want AI, they want their problems solved.
I had an interesting conversation recently about AI and how businesses actually perceive it.
It started with a simple question: what kind of AI content resonates with business owners?
The honest answer is that many of them see AI as gimmicky. And I get it.
AI is everywhere right now. CEOs mention it in earnings calls. Startups put it in pitch decks. Every product suddenly has an “AI feature.” A lot of it feels like hype, because most of it is.
But something came up in that conversation that I keep thinking about.
The problem isn’t AI itself. The problem is how it’s being sold.
The Mistake Most AI Companies Make
Most AI companies try to sell AI.
They lead with the technology. They talk about LLMs, agents, embeddings, fine-tuning, automation pipelines.
But business owners don’t wake up in the morning thinking “I really need some AI today.”
They wake up thinking:
- Why is this process taking so long?
- Why do I need this many staff to handle repetitive work?
- Why are we drowning in paperwork?
- Why are customers waiting days for a response?
They want problems solved. Not technology installed.
AI should simply be one of the tools used to solve that problem.
A Real Example
In that conversation, I mentioned a company I know that had a claims and invoicing process handled by around 90 staff.
It was slow, expensive, and highly manual.
The project that followed wasn’t pitched as “let’s install AI in your company.” It was pitched as “let’s fix your claims and invoicing bottleneck.”
AI just happened to be the technology that made the solution possible.
After the system was implemented, the team responsible for that process dropped from around 90 people to about 4.
That’s not an AI project. That’s a business transformation project. AI was just the mechanism.
The Infrastructure Nobody Talks About
Another thing that came up: the boring work.
Even when AI is the right solution, getting it to run inside a real business isn’t simple. You still need to integrate with existing systems, connect to calendars and internal tools, manage infrastructure, deploy models, monitor reliability, maintain updates, and make sure it doesn’t break existing workflows.
This is the unglamorous side of AI that actually creates value.
The flashy demo is easy. Running something reliably in production for non-technical users is the hard part.
The Computer Analogy
This is how businesses adopted computers too.
Nobody said “we want computers, let’s buy a bunch and figure out what to do with them.” They said things like “we need to process payroll faster” or “we need better inventory management.”
Computers were the tool that enabled those solutions.
AI should be treated the same way.
Businesses Don’t Want AI
They want lower costs, faster processes, fewer errors, and happier customers.
If AI helps achieve those outcomes, great. If something else works better, that’s fine too.
But any business that specifically says “we want AI” without a clear problem to solve is probably just riding the hype train.
The Direction Matters
Many AI companies approach the market from the wrong direction.
They start with “we have AI, what can we do with it?”
The correct approach is “what problem are you trying to solve?” and then you decide whether AI is part of the answer.
Sometimes it is. Sometimes it isn’t. And that’s perfectly fine.
A Closing Thought
The most successful AI implementations won’t be the ones with the most advanced models.
They’ll be the ones where nobody really talks about AI at all.
Because when the solution works properly, the technology disappears into the background. And the business just sees the result.
John Croucher builds practical software and AI systems for Australian businesses, focused on solving real problems with measurable outcomes.