Start here · 5 MIN READ · OCTOBER 14, 2026
AI agents or workflow automation? Start with the job.
Choose the right amount of intelligence for the work—and avoid adding an agent where a simple rule would do.
Use rules for predictable steps, AI for interpreting messy inputs, and an agent only when choosing the next step adds real value. Keep consequential actions behind review.
Start with a real unit of work
“Automate marketing” is too broad to build or measure. “Turn a completed discovery call into a draft brief for the account manager” gives you an input, an output, and an owner. Write those three things down before comparing tools. Also name what must never happen without approval: sending a proposal, changing a budget, publishing a claim, or deleting a record.
Separate rules from judgment
Rules are useful when the correct action can be described precisely: check required fields, match a customer ID, calculate a total, or route a request based on a selected region. AI can help when the input is unstructured: summarize a conversation, suggest a category, or draft a reply. An agent is useful when it must decide which tools or steps to try next. That flexibility introduces additional paths to test.
Build a small, inspectable example
Consider a quote request. A form submission triggers the workflow. Deterministic checks validate the email and service area. AI may summarize the customer’s request and suggest missing questions. A human reviews the draft. A final rule records the approved next step. The AI never invents a price or decides that the business can serve a location it has not confirmed.
Test failure before adding autonomy
Try a blank message, a duplicate, an unsupported service, and a message containing instructions to ignore your rules. Treat submitted text as data rather than authority. Require a structured output with allowed values; send invalid or uncertain results to a review queue. Do not turn an unexpected result into a silent default.
Measure useful work, not agent activity
Track valid requests processed, drafts accepted, corrections required, exception volume, and time spent reviewing. A longer chain of tool calls is not evidence of a better outcome. Expand autonomy only when your test set, logs, and operator experience support it. Start with one workflow owner who can pause the process and explain the last decision.
Try this next
Map one recurring task into rules, AI-assisted steps, and human decisions. Remove any AI step that cannot explain its value.
Put it into practice ↗Sources and further reading
Provider features and limits change. Use these original sources to confirm the setup you need.