AI entered the Maximo conversation in version 9.1. In 9.2, IBM is surfacing practical AI use cases across Maximo Application Suite, and I am asking what that means for day to day work. The question is not whether AI is interesting. It is whether it helps a technician, planner, reliability engineer, or Maximo administrator do useful work with less friction.
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That is how I view the new AI capabilities in Maximo. It is not a solve-all switch to be flipped, but it is a set of tools and, more importantly, a framework that can make existing processes easier. AI does not make Maximo better just because it is enabled. The useful part is where IBM’s Maximo team is applying it: work orders, problem codes, similar historical records, and reliability strategy work. That matters because the best Maximo improvements remove friction without forcing people to change how they work.

There Still Has to Be Value

AI is not free, quite the opposite, so time should be invested in using it well. It needs a clear connection to operational value, like faster troubleshooting, cleaner work order data, better reporting, reduced diagnostic time, or stronger reliability decisions. Using IBM’s delivered use cases as a guide, we can integrate AI into our Maximo lives and capture some of the value AI brings.

Natural Language Assistant

The most visible example is the Maximo Assistant. While it looks like the chat boxes showing up on sites across the web, this is not a general chatbot attached to Maximo. When enabled, it allows users to ask questions against Maximo data in plain language. For users who are not comfortable with SQL, advanced search, saved queries, or where clauses, that is meaningful.
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Instead of building a query, a user can ask, “Show me my open work orders,” and get back a result set that looks like a work queue. It lowers the barrier for getting useful information out of Maximo, but it is not perfect out of the box. Administrators need to ensure Maximo has a definition of what an open work order is and how ownership is defined. This is where the framework comes in. The key is setting expectations from the start on what it can answer, what it cannot, and how much the response depends on data quality. The framework also allows future releases and administrators to expand the capabilities.

Problem Code Recommendations

This one addresses a problem most Maximo customers recognize. Problem codes are valuable only when people use them consistently. Different technicians use different language, different sites build different habits, and too many records end up with vague or inconsistent values. If you have a problem code called “OTHER,” you know exactly how often that gets used.
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Problem Code Recommendations analyze the work order description and failure data, then suggest likely problem codes during work order entry. The user still chooses the final value. AI assists the decision and displays confidence, but it does not make the diagnosis on its own. I think a shorter list of two or three likely problem codes will help technicians use fewer clicks to find what they need and ultimately improve the quality of the data.

Final Thoughts

AI in Maximo should not be viewed as a single feature or a one-time project. These are two examples IBM has delivered and will continue to improve. As administrators, it is our choice to embrace these and other delivered AI features. That will require some investment. I recently published a blog about why we should move to the new role-based applications in some cases. Leveraging the AI features in those applications was one of my reasons.
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AI in Maximo is a toolset backed by an underlying framework that I think will only keep expanding. If you are ready to lean into the technology, adapt your work processes, and justify the added cost, AI can improve the Maximo experience. Start small. Pick a use case or two that justify the investment. Look at the data behind it. Decide whether it improves how people use Maximo. Not AI for the sake of AI, but AI that makes Maximo easier, faster, and more useful for the people who rely on it every day.

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