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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 RPAAI agents
    What it handlesA predefined path through predefined steps.The same path, plus the cases that fall outside it.
    Behavior on an exceptionStops, 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 expressedExplicit branches written for each condition anticipated in advance.Policy and context interpreted at run time, within a defined boundary.
    MaintenanceA 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.

    Two categories are worth naming, because they are often what "automation" means in an enterprise today. An integration platform, such as Workato, MuleSoft or Boomi, moves structured data between application endpoints on a trigger. Robotic process automation, such as UiPath, drives the screens of an application where no usable interface for machines exists. Both execute a path someone specified in advance, and both are good at that.

    Where they run out is the same place: a document nobody can map to fields, a case the branches do not cover, a wait of several days for a supplier or an approver, and the question of who decided what when an auditor asks a year later.

    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.

    Where to next

    Read deeper

    Product and platform pages on the same topic, drawn from the VeroTX knowledge base.

    Search everything in one place in the Research Center, or ask Veroli, which answers from the same knowledge base.