AI agent: definition, value and limits
AI agent Updated
Definition
An AI agent is a program that uses a language model to handle a task on its own across several steps. It plans, calls tools or systems, checks intermediate results and adjusts its approach. Think of it as a case worker who is given a goal, decides which steps are needed and operates various programs to reach it.
Why the Term Matters
Classic automation follows fixed rules. An AI agent, by contrast, can deal with intermediate steps whose order is not fixed in advance. That opens new flows but also carries risk, because the agent carries errors forward on its own. For mid-market process automation the rule holds: an agent is a tool for open tasks, not a replacement for a cleanly run rule-based flow.
When It Is Relevant
- A task needs several steps whose order depends on the intermediate result.
- Various systems or tools must be addressed in the flow.
- Inputs are unstructured and require interpretation.
- There are clear control points where a human can approve or stop.
When Not
When a flow has fixed rules and a clear order, pure RPA is more reliable, faster and cheaper. And when an error would be costly and no control is planned, an agent does not belong in the flow without approval, because it keeps acting on its own.
Industries That Use It
- Wholesale: take in a request, check it across several systems and prepare a quote draft.
- IT service: interpret incoming tickets, search fitting knowledge articles and draft a solution.
- Property management: capture tenant concerns, assign them and trigger the fitting steps.
- Travel and tourism: check booking requests, reconcile availability and prepare options.
Typical Use Cases
- Read an incoming request, query the needed systems and present a draft.
- Gather data from several sources and condense it into an overview.
- Run a multi-stage check and hand it to a human on doubt.
- Sift documents, classify them and suggest the next step.
- Run routine research across several systems and report the result.
Decision Guide
| Signal | AI agent fits | Alternative |
|---|---|---|
| Step order depends on the intermediate result | agent plans itself | RPA for a fixed order |
| Several tools in the flow | agent orchestrates | a single interface suffices |
| An error would be costly | only with approval | manual handling |
| All rule-based and stable | overkill | classic automation |
Example
A team lets an agent prepare incoming requests. It reads the request, queries two systems, drafts an answer and presents it with a source reference for approval. On doubt it stops and asks. The baseline is today's turnaround per request. This describes the method, not an asserted client metric.
Service Connection
An agent often complements an RPA build within process automation with AI, framed by process automation consulting.
Sources
This framing describes common practice when using AI agents in automated flows. Concrete implementation, control points and data protection depend on the case, the systems and the tools and must be checked case by case.