AI Automation Foundations

Automation should begin with a process that people can explain. Pick a repeated, bounded task and map its trigger, inputs, rules, outputs, owner and exceptions. Then decide which parts are deterministic and which require interpretation. Ordinary code is better for exact totals, identifiers and fixed business rules. An AI model may help classify or draft uncertain language, but its output remains something the surrounding system must validate. Draw the happy path and at least three failure paths. Ask what happens when an input is missing, duplicated, late or malicious. A useful automation does not merely produce an output; it leaves the organisation able to understand what happened and recover. Choose a low-consequence first workflow whose result can be reviewed before it affects a customer or irreversible record. Fictional worked example: Harbour Desk, an invented co-working space, receives general enquiry emails. The proposed workflow captures a permitted message, removes unnecessary personal details, asks an AI step to suggest one of four routing labels and drafts a short summary. Deterministic code checks that the label belongs to the allowed set. A staff member reviews the original message, label and summary before routing. Billing disputes and safety concerns always go to a person without automated action. Define success in operational terms. Harbour Desk wants to reduce manual sorting time while keeping misroutes visible and reversible. It will test on fictional or approved historical examples, measure label agreement and record correction effort. “Use AI everywhere” is not a goal. Neither is a vendor demonstration on three ideal messages. Include ordinary messages, ambiguous ones and cases the automation should decline. Set the boundary in writing. The model cannot approve refunds, promise availability, send external replies or create access credentials. The surrounding application owns authentication, authorisation, logging and execution. If a model suggests a tool action, the application still decides whether the action is allowed. Current function-calling systems use structured tool definitions, but tool availability is not permission to execute without checks. This independent course is not affiliated with or endorsed by any AI or automation provider. External accounts, API access, usage fees, workflow software and deployment are not included. Products and interfaces change; verify current official documentation before implementing. The deliverable here is a workflow map, not a production integration.