I do not ask AI every kind of question.

I find it most useful when the answer, or the information needed to reach it, already exists somewhere.

Software instructions are a good example.

In the past, I would search Google, open several pages, and look for the relevant section. The results often included outdated information, advertising, and explanations for different systems.

AI can organise that information into a shorter, clearer procedure.

I also use it in e-commerce research.

What prices are products selling for?
Which specifications appear most often?
How many listings have actually resulted in sales?

In these cases, market data already exists.

But AI should not be treated as the source.

Prices change. Markets move. Old and current information can easily become mixed together.

The actual data must still be checked.

AI is useful for collecting, comparing, and organising information. It reduces the time needed to reach sources that already exist.

A different kind of question begins with:

Should I buy this product?
Should I enter this market?
Should I start this business?

Data can support those decisions, but it cannot make them.

Purchase cost, profit, competition, shipping risk, experience, and long-term feasibility all matter.

The conclusion depends on what the person values most.

AI can arrange the factors.
It cannot decide which one should come first.

I use AI actively for searching, summarising, comparing, and checking.

But convenience is not the same as accuracy.

AI may confidently describe a menu, feature, or process that does not exist. It may combine old and new information.

So I keep one responsibility on my side:

to verify the source and judge whether the answer can actually be used.

Knowing what AI can handle—and what still requires human confirmation—is one of the first conditions for using it well.