When should we use an AI agent instead of a rule-based workflow?

Use a rule-based workflow when the steps and decision criteria can be defined in advance. Consider an AI agent when the task requires interpreting changing context and selecting between possible actions that are difficult to capture in fixed rules.

A rule-based workflow is usually the better fit for calculations, approval thresholds, mandatory checks and predictable routing. It is easier to test against explicit requirements and to explain why a particular path was followed.

An AI agent can be useful when handling varied requests, gathering information from different sources or deciding which permitted action to take next. Its usefulness depends on whether that flexibility improves the outcome enough to justify additional testing, monitoring and cost.

Not every task involving AI needs an agent. A fixed workflow can use an AI model to classify an email or extract information, then apply predefined rules to the result.

For example, a purchasing process might use AI to interpret a free-text request, fixed rules to check spending limits and a human approval step before placing an order. An agent may add value if it needs to investigate missing information across several systems.

RoboRana assesses the required flexibility, consequences of errors, operating costs and oversight needs. We favour the simplest approach that meets the requirements, combining agents and fixed workflows where that improves the process.