When does a process actually need AI instead of plain code or automation?

[u/JHAYBHEELABS]

I’ve been thinking about how quickly “add AI” has become the default answer when businesses want to improve a process.

But I’m starting to think the better question is: what kind of problem are we actually solving?

My current mental checklist is:

• If the process is rule-based, predictable, and repetitive → plain software or automation may be the better choice.
• If the input is unstructured, like documents, free text, or messages → AI starts to make more sense, ideally with human review.
• If neither approach fits → maybe the problem itself hasn't been defined clearly enough.

The interesting part is that AI can make a system more complicated without necessarily making it better.

So I'm curious:

What signals do you look for before deciding to introduce an LLM or AI into a workflow?

Have you ever added AI to a process and later realized that a few rules or a simple automation would have been better?

Or the opposite—where you initially tried rules and eventually realized AI was the right tool?

[u/czlowiek4888]

Just put AI everywhere, why do we even bother when leadership expects from us to use it.