Good AI starts with good taste

AI can generate options.

It cannot tell you which ones belong.

That is the part people keep underestimating.

They see the speed, volume and polish, then assume the hard work has disappeared. A model can draft the post, summarise the call, write the email, build the outline, create the image, suggest the campaign, analyse the data and produce the plan.

Useful, yes.

Finished, no.

Good AI starts with good taste.

Taste is not about being fancy. It is judgement. Knowing what fits and what does not. Knowing when something sounds too smooth. Knowing when a line is technically fine but emotionally false. Knowing when an idea is interesting but irrelevant. Knowing when the customer would not say it that way. Knowing when the output has become slop with a good haircut.

The machine can help you move faster.

It cannot care whether the result is right.

That is still your job.

This is why AI works best in the hands of people who already have standards. The better your taste, the more useful the tool becomes. You can see what to keep, what to cut, what to challenge and what to rewrite. You can give clearer direction because you know what good looks like.

Without taste, AI just increases output.

And more output is not automatically better.

A business can now produce more content than it can think through. More proposals than it can properly tailor. More reports than anyone wants to read. More strategy documents than it has appetite to execute. More automations than the team can trust.

That is not progress.

That is volume pretending to be capability.

Taste is the filter.

It asks: is this useful? Is it true? Is it specific? Is it ours? Will the customer recognise themselves in it? Does this make the work clearer? Does this reduce risk? Does this sound like us, or like the internet speaking through a spreadsheet?

These questions matter because AI is very good at average.

That is not an insult. Average is useful. A first draft, a structure, a summary, a checklist, a set of options. Average can save time if you treat it as a starting point.

The danger is treating average as finished because it arrived quickly and looked polished.

Polish is not quality.

A smooth sentence can still say nothing. A beautiful deck can still hide weak thinking. A confident answer can still be wrong. A neat automation can still create risk if nobody understands the work behind it.

This is where human-led matters.

The human sets the direction, owns the judgement and decides what good means. AI does the lifting, sorting, drafting, comparing, checking and speeding up. Then the human reviews, sharpens and takes responsibility.

That is not a slogan.

It is an operating model.

In marketing, taste decides whether the message sounds like the business or like everyone else. In sales, taste decides whether the follow-up feels human or automated in the worst way. In brand, taste decides whether the design creates trust or just decoration. In operations, taste decides whether automation helps the team or adds a clever new problem.

In AI work, taste is what stops the tool becoming the strategy.

You need someone in the room who can say, “No, that is not us.” Or, “That sounds impressive but it will not work.” Or, “The customer will not care about that.” Or, “This is the useful bit. Build around this.”

That is valuable.

It is also why experience matters. Taste is built through doing the work, seeing what fails, listening to customers, handling pressure, making mistakes and noticing patterns. You do not get it from a prompt library.

Prompts can help.

Taste leads.

The better question is not, “Can AI make this?”

It probably can.

The better question is, “Should this exist, and what standard does it need to meet?”

That is where businesses will separate. Not by who has access to the tool. Everyone has access to the tool. The difference will be who has the judgement to use it well.

Good AI does not remove the need for taste.

It exposes whether you had any in the first place.

That is why I am more interested in operating standards than prompt tricks. What should never go out? What does good sound like? What proof do we need? What risks must be checked? What would make this feel false? These are not technical questions first. They are business questions.

Answer those, and AI becomes a useful assistant.

Ignore them, and it becomes a very fast way to lower your standards while feeling productive.

That is the uncomfortable truth. AI will not save a business from weak taste. It will simply make that weakness more visible, more frequent and much easier to publish.