If you can write the rule on a sheet of paper, you need a rule. AI is for when the decision depends on a text, a context or a judgement.
A rule first
A rule always does the same thing. It is reliable, testable and costs almost nothing to run. “If the amount exceeds this threshold, ask for approval” doesn't need artificial intelligence. I don't use AI where a simple rule will do: it is more reliable and cheaper.
When AI really adds something
As soon as the information arrives as free text: reading a document, understanding an incoming request, classifying it, preparing a first reply. There, writing all the rules would be impossible, and a model saves real time.
The good sign: today a person does this work by reading, and their judgement follows a logic they could explain.
And an agent?
An agent chains several actions and decides the next one itself. It has more freedom, so it needs more supervision. It's an area I'm experimenting with, and I'll say so plainly: promising, but rarely the first choice. Most needs are solved with a clear workflow and a model called at a single step.
Stay in control
Whatever the choice, I ask AI for structured outputs that the system can check before using them. When the stakes require it, a person approves. And we measure: time saved, error rate, what the team still corrects.
Three questions to decide
Can you write the rule? Then a rule. Does the decision depend on a text or a context? Then a model, at one precise step. Do you need to chain actions you can't predict in advance? Then perhaps an agent, with guardrails.