Systems like ServiceNow with a workflow engine organize tasks, assign responsibilities, execute rules, and coordinate systems. These type of workflow engines coordinate the flow of work.
AI agents operate at a different level. Their value appears when someone needs to interpret information, generate options, or make decisions.
IT service desk reviewing an incident.
An analyst preparing a proposal.
In these situations, the challenge is not moving a process to the next step forward. The challenge is figuring out what to do.
Confusing these two roles can lead to unclear architectures. Trying to turn AI agents into process engines or attempting to force workflow platforms to perform cognitive work.
Workflows perform best when the work is already defined.
Agents perform best when the work requires interpretation, reasoning, or decision making.
A useful way I found to think about this is as AI Agents assist with thinking and workflows orchestrate work.
The agent proposes, interprets, or prepares a decision.
The platform executes, records, and coordinates the flow.
Two different layers of the same system.
This is a shift in architecture, so it is not anymore about the full automation of processes, it is about separating who helps with thinking and who organizes the work.
Jesús Melendez 