One of the easiest mistakes to make with AI is putting it into a process that was already broken. You automate it. And now you have a broken process that runs faster.
That is not progress. It is just faster chaos. I think about this whenever I look at how businesses work.
A business owner might say:
“We need AI.” But sometimes what they actually need is to stop doing something the same way they have been doing it for five years. Maybe five people are copying information from one spreadsheet to another.
Maybe customers are sending questions through three different channels. Maybe reports are being created manually every month. Maybe nobody knows where the important information lives.
Then someone says:
“Let's add AI.” But AI is not the first question. The first question is:
“Why are we doing this this way?”
That question matters. Because technology is very good at helping us repeat things. It is not always good at deciding whether the thing is worth repeating.
This is one of the biggest lessons I’m learning as I work more deeply with AI. Before you automate something, understand it. Before you add a tool, understand the problem.
Before you build a system, understand the outcome you want. I think about this in three simple ways. Will it make money?
Will it save time? Will it improve quality? If the answer is none of the three, why are we doing it?
That simple filter can eliminate a surprising amount of unnecessary work. For example, imagine a business spends ten hours a week creating a report that nobody actually reads. You could build an AI system to create the report in ten minutes.
That sounds impressive. But maybe the real solution is to stop creating the report. The biggest improvement was never automation.
It was elimination. This is why I don't think businesses should start their AI journey by asking which tools to buy. Start by looking at the work.
Where does time go? Where do mistakes happen? Where are people repeating themselves?
Where are customers waiting? Where is information trapped? Where is the business doing something manually simply because nobody has stopped to question it?
Those are the places to investigate. Then AI becomes much more useful. Because now you are not adding technology for the sake of technology.
You are using it to improve something that already matters. That is also how I want to approach my work with clients. I don't want to walk into a business with a favourite AI tool and try to find somewhere to use it.
I want to start with the business. Find the problems. Understand the workflow.
Look for the opportunities. Then recommend the technology. The tool comes last.
The problem comes first. That might not sound as exciting as the latest AI demo. But it is much more useful.
Because at the end of the day, nobody pays you for having AI. They pay you for making something better. AI is powerful.
Knowing what to use it for is more valuable.
