AI Can Make It Look Good. But Does It Fit?

The problem is not new. Long before AI, organisations built websites from generic templates that did little to communicate who they were or what they stood for. The result could look perfectly acceptable and still feel completely wrong for the organisation.

You can take an existing design, give it a fresh coat of paint, and call it your own. Or you can make deliberate choices about what you want to communicate, how the experience should feel, and how you want your organisation to be perceived.

For many things, “good enough” really is good enough. Not everything needs to be custom-made, complex, or overdesigned.

But that choice comes with a trade-off: the quality you accept becomes part of the quality people associate with you.

Imagine you are preparing to run a marathon and find the perfect pair of shoes on sale.

They look great and cost a fraction of the original price. There is just one problem: they are one size too small.

You try them on. There is some pressure, but it does not seem too bad. For that price, you convince yourself they are good enough.

At the starting line, they still look fantastic. For the first few kilometres, you might not even notice the compromise.

Then they start to hurt. You slow down. Your attention shifts from the race ahead to the pain of every step. Your energy goes into compensating for something that was never designed to fit you in the first place.

The shoes still look good, but appearance was never the goal. You entered the race to perform.

Suddenly, the money you saved no longer feels like much of a saving. What looked like a smart shortcut has become the thing holding you back.

The same is true for digital products.

A template can look good, and AI can make it faster and cheaper to produce. “Good enough” might even get you to the starting line.

But having the shoes is not enough. They need to fit.

Does this mean investing in the most expensive, highly tailored solution from the beginning? Not necessarily.

Start with what you need. Choose something that meets the essential criteria, use it, and learn from it. As your needs grow and the stakes become higher, invest accordingly.

The point is not that custom solutions are always better, or that templates and AI are inherently bad. It is about choosing the right solution for the problem you are solving and the stage you are in.

I reduce that to three questions.

What purpose must it serve?

A solution can look polished and still fail at its job. Who will use it? What must it help them do? What does it need to communicate? And does it work in the environment for which it was created?

The marathon shoes might look fantastic. But if you cannot run a marathon in them, they have failed their function.

Good design is not simply about appearance. It is about the relationship between form and function.

Can it be tested and adapted?

Every idea sounds good until you test it. Put the first version in front of real people, observe how they use it, gather feedback, and improve what matters.

A solution does not need to be perfect from the beginning. It needs to give you room to learn and adapt.

Is it right for where you are now?

Sometimes a template is enough. Sometimes an AI-assisted solution is enough. Sometimes a custom solution justifies the investment.

What is right for an organisation testing its first idea may be wrong for one entering a new market or operating at an established level.

The right solution matches your current needs, resources, and ambitions. Invest too early and you may waste time and money. Wait too long and the solution may start holding you back.

AI can make it faster and cheaper to create something that looks like a finished product. But when everyone has access to the same tools, using the tool is no longer the advantage.

The advantage is understanding the problem, learning from real use, and knowing when the solution needs to evolve.

AI can get you to the starting line faster. But getting there was never the goal.

The goal is product fit.