Does This Workflow Need Automation or an AI Agent?

A request to “add an AI agent” is often a request to remove frustrating work. Before choosing the technology, describe the work itself. Which information arrives, which decisions are predictable, what changes from case to case and what happens when the process cannot continue?

This description may reveal that a straightforward integration is enough. It may also reveal a narrow task where AI can help interpret unstructured information. The useful starting point is the amount of judgment and flexibility the workflow requires.

Separate rules from interpretation

A fixed rule might send an approved form submission to the correct sales queue based on the selected country. An interpretation task might summarize a long email or suggest which service best matches a loosely written enquiry. A business decision might approve a discount or commit to a delivery date.

These steps can sit in the same workflow while having different controls. An AI-generated summary does not automatically need permission to approve the quote that follows it. Make the boundary explicit in the design.

Understand what an agent changes

Anthropic’s discussion of effective agents distinguishes predefined workflows from systems in which a model directs its own process and tool use. That is an architectural distinction, not a guarantee of better results. More flexible behavior also gives the team more behavior to evaluate and operate.

Ask whether the task genuinely requires selecting different steps dynamically. If the sequence is known and the conditions can be expressed clearly, a fixed workflow may be easier to inspect. If the input requires interpretation, a model can assist one stage without controlling the entire process.

Map a concrete example

Consider a service business receiving project enquiries. A simple first workflow could collect the form, validate required fields, create a CRM record and notify the owner. An AI step could draft a short summary for staff. A later agent might gather approved background information or suggest questions to ask next.

Each addition should have a defined purpose and a way to assess its output. Start with the smallest change that addresses the problem. Avoid granting broad access merely because a tool can connect to many applications.

Define action permissions before tools

List what the system may read, propose and change. Use separate categories for actions that can happen automatically and actions requiring a person’s approval. A draft response, an internal label and a refund are different levels of commitment.

• Which records and documents can the workflow access?
• Can it create records, or only suggest changes?
• Which actions must be approved by a named role?
• What happens when information is missing or contradictory?
• How can staff stop the workflow and inspect what happened?

Put these rules into the actual application and account permissions where appropriate. A sentence in a prompt should not be the only barrier protecting an important business action.

Test normal work and exceptions

Collect a representative set of tasks and define acceptable outcomes. Include incomplete inputs, duplicate requests, unavailable services and instructions embedded in material the system should treat as data. Test whether the workflow asks for help when it cannot complete the task reliably.

Compare the result with the current process. Record review time, correction work, unresolved cases and operating cost. A shorter automated step may still create extra work elsewhere, so evaluate the whole handoff.

Assign an operating owner

Someone needs to monitor failures, update instructions, manage access and approve changes as the business evolves. Decide how changes to a model, connector or source document will be tested. Keep a manual route available for the work that still needs to be completed during an interruption.

LeapHover can help map the process and choose between automation, an AI-assisted step and a more flexible agent. Bring a few real examples of the work, with sensitive details removed, and define what a useful completed result looks like.