Traditional automation works best when rules and exceptions are known. AI agents become relevant when context must be interpreted, sources combined and an action proposed — always within clear boundaries.
Responsible evolution requires three layers: trusted data, observable processes and decision governance. Without them, an agent merely accelerates inconsistencies that already existed.
Starting small is an advantage. A bounded use case with human review and quality metrics provides enough learning to decide whether the solution should be expanded, redesigned or stopped.
A question for the next decision
What evidence must be available for your organisation to move forward with confidence — and which risk must be reduced first?