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What is the difference between AI agents and workflow automation?
Both move work forward. They differ in what happens the moment a case stops looking like the one the process was designed for.
The short answer
Workflow automation and robotic process automation move data between steps that someone specified in advance. AI agents run the work itself, including the decisions, exceptions, and approvals in between. Rule-based bots break when a case falls outside the script; an agent reasons over context and policy, escalates the exception to a person, and keeps going.
Side by side
| Workflow automation and RPA | AI agents | |
|---|---|---|
| What it handles | A predefined path through predefined steps. | The same path, plus the cases that fall outside it. |
| Behaviour on an exception | Stops, errors, or routes to a queue for a person to unpick. | Reasons over context and policy, escalates to a person, and continues. |
| How rules are expressed | Explicit branches written for each condition anticipated in advance. | Policy and context interpreted at run time, within a defined boundary. |
| Maintenance | A change in a screen or a form usually means rebuilding the script. | Changes are absorbed where they do not alter the intent of the stage. |
When each one fits
Deterministic, high-volume, low-variance tasks are a good fit for rule-based automation, and replacing that with an agent adds cost for no gain. Processes with judgment, exceptions, and approvals are where scripted automation tends to leak work back to people, and where agents earn their place. Most enterprises end up running both.
Where VeroTX sits
VeroTX runs agent-based work as a named sequence of stages with owners, policy checks, and approval points, which VeroTX calls a WorkStream Playbook. The agents act inside those stages rather than inside a scripted click path, and each action is recorded in the Execution Ledger.