What is an AI agent for IBM Maximo?
The short answer
An AI agent for IBM Maximo is software that reads Maximo data such as meters, work history and failure codes, reasons about what should happen next, and prepares the action inside Maximo: for example, a drafted work order with a job plan, crew and reserved parts. Well-governed agents need a person to approve each action and record every decision in an audit trail.
AI agents vs alerts vs assistants in Maximo
| Predictive alert | Chat assistant | AI agent | |
|---|---|---|---|
| What it does | Flags a pattern | Answers a question | Plans and prepares the work |
| Output | A notification | Text on screen | A drafted work order, reservation or request in Maximo |
| Who does the last mile | A planner, by hand | The user, by hand | The agent drafts; a person approves |
| Learning | Usually stops at the alert | None | Outcomes feed back into the next decision |
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What an AI agent needs from Maximo
- APIs and permissions. The agent should work through Maximo’s own APIs and never do more than the approving user is allowed to do.
- History it can learn from. Work orders with valid problem, cause and remedy codes, meters, and a consistent asset hierarchy.
- Context. Job plans, spare parts, crew calendars and planned outages, so a proposal is something a planner can actually approve.
AI agent autonomy should be a setting, not a leap of faith
Good agent products let you choose how much they do, per action type, asset class and site:
- Inform: analyse and explain only.
- Recommend: suggest actions; people create the work.
- Draft for approval: prepare complete work orders that a person approves. This is the sensible default.
- Act within limits: complete low-risk, reversible actions on their own, never on safety-critical assets.
A worked example
A point machine’s throw time drifts from 3.80 to 4.28 seconds. Maximo’s alarm is set at 5.0 seconds, but similar machines failed between 4.6 and 4.9. An agent spots the trend overnight, matches it to past failures, drafts a work order for that night’s maintenance window and reserves the parts. A planner reviews the evidence and approves in Maximo at 07:05. Planning effort drops from about 45 minutes to 8, and the failure never reaches the morning peak. (Illustrative example, synthetic data.)
That is the model behind Perimo Asset Agents, which work inside Maximo 7.6, MAS and other EAMs with human approval by default and a tamper-evident audit trail.