Begin with predictable steps
If inputs and decisions follow clear rules, conventional automation may be enough. Moving a valid form into a system, sending an approved notification, or applying a fixed routing rule does not inherently require a language model.
Add AI where interpretation matters
AI can help with unstructured language, document understanding, classification, and response drafting. Define acceptable outputs and evaluate against representative examples. When a step affects a customer or changes a business record, decide which approvals should remain with people.
Give agents a bounded job
An agent may be useful when a task requires selecting actions or coordinating tools based on changing context. Give it limited permissions, explicit stopping conditions, and clear escalation rules. A dependable result is the success measure.
Design the fallback
A working system needs a path for missing information, integration failures, and uncertain outputs. Log what happened, preserve the request, and route it to the right person. Measure how often this path is used and include that effort in the economics.
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