An AI Agent is a software component capable of interpreting information, reasoning about a situation, and taking or recommending actions that influence how a business process is executed.
It may perform a task, contribute to a decision, determine which path a process should follow, interpret an incoming event, or assist a human participant.
In the case of a task, this does not mean that an AI Agent will always replace a usual automated task.
Consider a customer email containing an account number and a request for information.
A usual automated task can reliably retrieve information from a system when it receives the expected structured data. Its behavior is deterministic: given the same conditions, it follows the same predefined rules.
An AI Agent can do something different. It can read an unstructured email, understand what the customer is asking, identify the relevant information and determine what should happen next.
But that additional capability comes with a trade-off: interpretation and reasoning introduce uncertainty. The Agent can be wrong.
This risk can nevertheless be evaluated and managed. An Agent can be tested against representative business cases, while the process can define when its output may be used automatically and when human validation is required.
The acceptable level of uncertainty depends on the business consequences of being wrong.
Introducing AI Agents into a business process therefore changes more than the way individual tasks are performed.
Decisions that were previously based entirely on predefined rules may now involve interpretation. Activities previously performed by humans may now be performed by Agents, while human intervention may move toward validation or exception handling. New controls and alternative paths may be required to manage uncertainty.
And changes in one part of the process may have consequences elsewhere.
An AI Agent can successfully perform its assigned task without necessarily improving the process around it.
A faster activity may create a bottleneck downstream. A more sophisticated automated decision may require additional controls. Removing a human task may create the need for human intervention somewhere else.
Business processes may therefore increasingly combine human participants, deterministic automation and AI Agents — each with different capabilities and constraints.
The question is not only what an AI Agent can do, but where and how its capabilities should be introduced into the business process.
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