AI Agent or Workflow? Where Should Businesses Draw the Line?

A customer calls the company because the air conditioning isn't working. They don't know exactly which unit is affected. All they can say is that the meeting room is hot and the unit is making a strange noise.

An AI phone agent can ask which building they're in, how long the problem has been happening, and whether they can read the unit's identification number. At the end of the call, it can summarise what was said.

After the call, though, the system has more work to do. It needs to check the company's rules, record the report, and notify the right employee or contractor. These steps are worth planning in advance.

What should an AI agent be free to decide?

AI agents are getting a lot of attention. That's understandable: an agent can interpret requests phrased in many different ways and ask follow-up questions based on the answers it receives.

Customers rarely provide every necessary detail in the same order. Some start with the symptoms; others give the location first. Some don't know which details would help the team.

This is where an agent's flexibility is useful. During the conversation, it can gather missing information, interpret the request, and suggest how to classify it.

But it can also make mistakes. It might misunderstand a sentence, record the wrong location, or draw a conclusion that a person would assess differently. It won't necessarily give the same answer to similar calls, either.

That's why it's important to define the limits of the agent's decision-making. It might ask for a missing detail, for example. But if it can't determine whether a case is urgent, the company can require it to transfer the call to a person.

After the call comes the workflow

Most companies already have a way of handling customer requests. They decide where information should be recorded, who is responsible, and when someone needs to be notified separately.

That process can be described in a workflow.

In the air-conditioning example, the workflow can check whether all required details are available after the call. It can then create a ticket in the appropriate system and notify the responsible employee or contractor according to the company's rules. If a required detail is missing, the case can be sent for further review.

The exact steps differ from one company to another. In some cases, the system can forward a request immediately. In others, approval is needed first.

The AI agent helps with the conversation; the workflow moves the case forward through the steps defined by the company.

What happens when something goes wrong?

A workflow doesn't make a process error-free. The agent may misunderstand the caller, the customer may give an incomplete answer, or the ticketing system may be unavailable.

These situations need to be considered during design. If a ticket can't be created, who should be notified? Where should the call summary be retained? When should the system retry, and when should a person take over?

The same applies to uncertain AI responses. An agent can flag that it hasn't found enough information. The workflow can then require human review before anyone acts on the response.

Start by examining the existing process

When considering an AI agent, it helps to follow one specific case from start to finish. What happens between a request coming in and someone actually starting to handle it?

That can reveal where AI would help interpret a conversation or free-text request. It also shows where the company's existing rules must apply and where a person should make the decision.

One process is enough to get started. Take an incoming customer call, for example, and identify what you'd give the agent responsibility for, what the workflow would check, and who it would notify if something were missing.

Let's look together at where an AI phone agent could help with incoming calls and which rules your process needs.