IBM Maximo® Application Suite 9.2 brings artificial intelligence into maintenance as a practical assistant that technicians can use in their everyday work. IBM Maximo® can connect information about asset condition, work orders, measurements, and inspections. In supported scenarios, technicians in the field can retrieve the information they need by asking a natural-language question, including by voice.
This does not mean that Maximo will automatically predict every failure as soon as the new version is installed. Practical value depends on three things: selecting an appropriate use case, having sufficiently reliable data, and designing and operating the environment correctly.
What is genuinely new in Maximo 9.2
In version 9.2, IBM does not place AI in a separate analytics tool that users must open outside their normal work. The new capabilities are incorporated directly into reliability, planning, maintenance execution, and field-service workflows.
Condition Insight: understanding asset condition more quickly
Maximo Condition Insight uses available information such as measurements, alerts, inspections, work orders, and reliability strategies. Its role is to summarize the condition of an asset, highlight important changes, and recommend possible next steps.
For maintenance staff, this can mean less time spent searching across several screens. Instead of reviewing failure history, the latest meter readings, and inspection results separately, they can receive a clearer summary of what is happening to the asset and why the situation deserves attention.
AI output is still only an input to the decision-making process, not a substitute for engineering judgement. A recommendation must be traceable — AI in Maximo displays the relevant passage from the equipment manufacturer's documentation — assessed in the context of the operation and appropriate to the criticality of the asset.
An assistant for field technicians
Maximo Assistant on Mobile enables technicians to search for information using natural language. They can ask about asset history, previous interventions, or other information needed to complete their work. The aim is not to add another chat window, but to shorten the path to information the organization already holds in Maximo.
Version 9.2 also extends Maximo Visual Inspection. A vision model can inspect an image directly on a mobile device and flag, for example, a visible defect or an incorrect condition. Local processing is particularly useful where connectivity is unreliable or where image data should not be sent outside the worksite.
The availability of these capabilities always depends on the licensed applications, the chosen configuration, and the supported architecture. The label “MAS 9.2” alone therefore does not mean that every listed capability is automatically enabled for an organization.
Planning through an ordinary question
AI also plays a role in work planning. A planner can explore scenarios such as “what happens if we increase the capacity of this shift?” or “how will the plan change if critical work is prioritized?” The purpose is not unsupervised automatic decision-making, but a quicker comparison of alternatives when priorities, capacity, or workforce availability change.
Connecting an organization’s own AI tools through MCP
IBM also presents an MCP Server in connection with Maximo 9.2. In simple terms, the Model Context Protocol is a standardized way for an AI assistant or agent to use precisely defined functions of another system.
An organization can therefore connect its own assistant to Maximo Manage APIs without building every integration entirely from scratch. Permission management, auditing of completed operations, and a clear distinction between what an agent may read and what it may change remain essential. MCP is neither magical automation nor a replacement for secure integration. It is another way to provide AI with controlled access to enterprise processes.
Clear results require clear data
Maximo 9.2 can work with more context than earlier versions, but no version can entirely compensate for poor input data.
If the same failure is described in work orders as “drive” once, “motor not running” another time, and simply “fixed” on a third occasion, the system has limited ability to identify a recurring problem. Assessing asset condition is similarly difficult when measurements are assigned incorrectly, units are missing, inspections use inconsistent answers, or work orders are not linked to a specific asset.
Before introducing AI, it therefore makes sense to review in particular:
- the structure of locations and assets,
- how failures, causes, and remedies are recorded,
- the completeness and clarity of work orders,
- the quality of measurements, inspections, and timestamps,
- the links between an identified problem, the work performed, and the outcome of the intervention.
The objective is not a perfectly clean database. The objective is data that is consistent enough for people to understand and for the system to derive useful relationships safely.
Installing MAS is a technical project in its own right
Moving to Maximo Application Suite is not a routine update of a single application on an existing server. MAS is a suite of containerized applications running on Red Hat® OpenShift®. In addition to Maximo itself, the project must prepare and align infrastructure, storage, networking, DNS and certificates, user identities, databases, licensing, backups, and environment monitoring.
IBM also requires cluster-administrator privileges for installation into an existing cluster because MAS uses resources across namespaces. MongoDB is a prerequisite for the Suite itself, while Maximo Manage introduces additional application and database requirements.
Version compatibility is equally important. The platform version, operators, IBM Maximo® catalog, and installation tools must be compatible. Automation through MAS CLI or operators simplifies many steps, but it cannot eliminate errors in network configuration, storage, certificates, access rights, or cluster sizing.
There is a reason for this complexity. The platform provides scaling, service isolation, automated container orchestration, and high-availability options. At the same time, it requires knowledge that goes well beyond administering a traditional Maximo Asset Management installation. It is therefore useful to separate three parts of the project:
- preparing and validating the Red Hat OpenShift platform,
- installing and configuring Maximo Application Suite and the selected applications,
- migrating data, integrations, customizations, and operational processes.
When these parts are treated as a single installation step, identifying the cause of problems becomes harder and the risk of project delays increases.
How to begin so that the new capabilities deliver value
The safest approach is not to enable every available option at once. It is better to select one specific problem with a measurable outcome. Examples include recurring failures on a selected production line, faster retrieval of asset history, visual inspection of a particular defect, or improved work planning when technicians are in short supply.
A practical sequence can look like this:
- verify the readiness of the infrastructure and the current Maximo version,
- select a process in which time or availability is demonstrably being lost,
- review the data required for that specific use case,
- deploy a limited pilot with clearly identified users and responsibilities,
- compare the result with the original situation before expanding the solution.
This approach helps distinguish whether an issue lies in the technology, the data, or the process configuration. It also gives management and maintenance teams concrete evidence for decisions about further development.
Maximo 9.2 is an opportunity, not a finished result
IBM Maximo® Application Suite 9.2 illustrates the direction of enterprise asset management: from recording work to continuously interpreting data and supporting decisions directly in operations.
The greatest value will not necessarily go to the organization with the largest number of AI functions enabled. It will go to the organization that combines a well-designed platform, understandable maintenance data, and a concrete operational need.
At 12servis s.r.o., we help organizations design, install, administer, and develop IBM Maximo®. Preparation can also include an assessment of the current environment and maintenance data so that it is clear which MAS 9.2 capabilities have genuine relevance for a particular operation.