Simple automation is right more often than people think. The line is whether a step needs judgement.
Trigger-action tools move data between two applications when something happens. They are reliable, inexpensive, and the right choice for simple, deterministic hops. Wherever a tool like that solves the problem, use it.
The line is judgement. The moment a step needs to read a document, decide what kind it is, and draft a response, a trigger-action tool cannot do it well. That is where an AI layer earns its place.
The strongest systems combine both. A deterministic backbone handles routing, retries, logging and the audit trail in plain code, and AI sits only at the judgement steps. That split is why the system keeps working when a model has a bad day, because the AI step fails into an exception queue rather than silently corrupting your data.
Cost should be measured honestly. A trigger-action subscription is cheap, but if it still leaves a person reading and re-typing, the loaded cost of those hours is the real number to compare against an AI build.
A good supplier will tell you when a simple tool is enough and build the AI layer only where it pays for itself. That is the test of whether you are being sold a solution or a system you actually need.
