“AI agent” is doing a lot of work in marketing decks right now. Stripped of the hype, an agent is software that can take a goal, decide on a few steps, use your tools or data to act, and hand back a result. A human stays in the loop where it matters. For a mid-market operation, the real question is where agents earn their keep.
Where agents actually help
- Triaging and routing an incoming maintenance request or support email so it lands with the right priority and context.
- Drafting a first-pass quote, summary, or report grounded in your ERP, ready for a person to review and send.
- Watching for the orders, invoices, or readings that fall outside the rules, and surfacing them for a human to handle.
Where a simple script is smarter
If a process is fully deterministic, with the same inputs and the same steps every time, you usually do not need an agent. A reliable automation or RPA bot is cheaper, faster, and easier to audit. Agents earn their cost when there is genuine judgment or variability involved.
Don't deploy a model where an ‘if’ statement will do, and don't deploy an ‘if’ statement where the work genuinely needs judgment.
The part everyone skips: governance
Before an agent touches production data, you need to know what it can access, what it logs, and how a human stays in control. That is not bureaucracy; it decides whether the agent ends up a tool your team trusts or a liability your auditors flag.