Maximo Mobile 9.2: Crew Work Orders, AI Assistant, and Offline Visual Inspection

Maximo Mobile has been steadily maturing since IBM shifted from the legacy Maximo Everyplace to the MAF-based mobile application. MAS 9.2, released June 25, 2026, delivers the most significant mobile update yet. Three headline features change the game for field service teams: crew-based work order execution, an AI assistant that brings natural language interaction to the field, and offline visual inspection running AI models locally on iOS devices.

This article covers each of these capabilities in depth, explains the configuration requirements, and provides practical guidance for rolling them out to your field organization. We also cover the new QR-code onboarding feature, the expanded platform support that brings Maximo Mobile to Windows devices via the Microsoft Store, and the enhanced mobile dashboard that gives technicians a centralized view of their daily assignments.

Crew-Based Work Order Execution: A New Paradigm for Field Teams

The most operationally impactful mobile feature in MAS 9.2 is Work Order Crew Support. Previous versions of Maximo Mobile treated every technician as an individual: individual work order assignments, individual labor reporting, individual actions. This worked for solo technicians but created significant friction for crew-based operations where a supervisor leads a team of technicians to complete work orders together.

Consider a typical scenario: a four-person crew is assigned to replace a transformer at a substation. In previous versions, each technician had to individually find the work order, start work, and report labor. The supervisor had to call each technician to confirm they had started, track who was working on what, and manually consolidate labor entries at the end of the day. With four people on one work order, that is four separate start actions, four separate labor entries, and four separate completion steps, all for a single job.

MAS 9.2 introduces crew-assigned work orders directly in the Maximo Mobile Technician app. Crew members and supervisors can now view work orders assigned to their crew, perform actions on behalf of the entire crew, and report labor collectively. This eliminates the tedious process of each crew member individually starting, stopping, and reporting labor on the same work order.

How Crew Work Orders Work: All crew-related work orders appear under a new "Assigned work for crew" list within the My Schedule (Technician) application. This list is populated based on crew allocation, supervisor assignment, and the scheduled time window. Crew members see the same work orders regardless of which individual is viewing the list, ensuring the entire team has visibility into the day's assignments.

Crew members can perform the following actions directly from the mobile app:

• Start Work and Stop Work for the crew
• Start Travel and Stop Travel for the crew
• Accept or Reject work orders on behalf of the crew
• Reassign work orders to individual labor (note: crew-to-crew reassignment is planned for MAS 9.3)
• Complete work orders at the crew level or individual level

The Crew Lead (supervisor persona) has extended control. Supervisors can manage work on behalf of their teams, reassign work orders between crew members, and oversee multiple crews simultaneously. This is particularly valuable for organizations with large field teams where a single supervisor coordinates multiple work crews across different locations.

Labor Reporting: The labor reporting interface has been enhanced with a crew mode toggle. When crew mode is switched on, labor entries apply to the entire crew. When switched off, the technician reports only their personal labor. This flexibility means that on a mixed work order where some tasks are crew-based and others are individual, technicians can switch between modes as needed without leaving the work order.

To enable crew support:

# Configuration steps in Maximo Mobile Administrator
1. Navigate to Mobile Administrator > Technician App Configuration
2. Enable "Crew Operations" toggle
3. Configure crew-based workflows:
   - Set default labor reporting mode (Crew or Individual)
   - Define which actions require supervisor approval
   - Configure crew visibility rules (same site, same supervisor, etc.)
4. Save configuration and push to mobile devices
5. Verify crew assignments exist in Maximo Manage (Crew tab in Labor application)
6. Test with a sample crew in a non-production environment

Operational Benefits: Organizations that adopt crew-based mobile execution can expect several tangible benefits. Work order execution becomes faster because a single action starts work for the entire crew instead of requiring individual starts from each member. Labor tracking becomes more accurate because crew mode captures collective effort without requiring each person to remember to enter their time separately. Coordination between crew members and supervisors improves because everyone sees the same work order list and status in real time. And the administrative burden of end-of-day labor reconciliation drops significantly because there are fewer individual entries to review and correct.

AI Assistant on Mobile: Natural Language in the Field

The Maximo Assistant has evolved in 9.2 from a chatbot into a context-aware agentic teammate. On mobile, this means technicians can interact with Maximo using natural language instead of navigating through application menus and saved queries.

A technician can simply type or speak: "Show me all high-priority work orders assigned to me for pump assets." The assistant parses the query, applies the appropriate filters, and returns the result set. No need to navigate to the Work Order Tracking application, open the filter dialog, set priority to 1-3, set assignment to self, and search for pump in the asset description. One query replaces a multi-step navigation process that could take 30 seconds or more, reduced to a few seconds of typing or speaking.

The AI Assistant on Mobile supports queries across more than 10 business objects, including work orders, assets, locations, job plans, inspections, and inventory records. It respects Maximo security, meaning technicians only see data they have permission to access. The assistant inherits the same role-based access controls that govern the rest of the application.

Key capabilities include:

• Finding work orders by priority, asset, location, status, or date range
• Retrieving asset history and failure patterns
• Looking up job plan steps and task lists
• Searching inventory by item number, description, or storeroom
• Getting AI-generated asset insights and alert context
• Asking for help with work order procedures and safety steps

The assistant also provides configuration guidance. A new technician who is unsure how to complete a specific work order step can ask the assistant for help, and it will provide step-by-step guidance based on the job plan, safety procedures, and asset history. This is particularly valuable for organizations facing workforce turnover, where newer technicians need more hand-holding than experienced staff. Instead of calling a supervisor or digging through documentation, the technician gets immediate answers from the assistant.

Multi-Turn Conversations: The assistant supports multi-turn conversations, meaning a technician can ask follow-up questions without restating context. For example:

Technician: "Show me work orders for pump PUMP-1001"
Assistant: [Returns 5 work orders]
Technician: "Which of these has the highest priority?"
Assistant: "WO-12345 has priority 1 and is due tomorrow at 5 PM"
Technician: "What was the last failure on this pump?"
Assistant: "The last failure was a bearing failure on June 12, 2026. 
          The root cause was identified as inadequate lubrication."

Privacy and Security: The AI Assistant is grounded in your operational data. It does not send sensitive asset data to external services without governance. The assistant respects Maximo security, permissions, and access controls by design. Role-aware operational access means every team member sees what they need, in the way they need to act on it, without exposing data outside their permissions.

Offline Visual Inspection: AI Defect Detection Without Connectivity

Maximo Visual Inspection (MVI) has been available as a separate application for several releases. MAS 9.2 brings visual inspection directly into the Maximo Mobile app with a crucial enhancement: offline capability. Technicians can take photos of equipment in the field, and locally running AI models on their iOS devices analyze the images for defects and abnormal conditions without requiring network connectivity.

This is a significant advancement for field operations. Previously, visual inspection required uploading photos to a server for AI analysis, which was impossible in remote locations without connectivity. With offline MVI, a technician inspecting a transmission tower in a rural area can photograph equipment, have the AI model identify potential defects (rust, cracks, missing bolts, oil leaks), and flag them for follow-up without ever connecting to a server.

How It Works: The MVI model is downloaded to the iOS device during the mobile app synchronization process. The model runs locally using Core ML, Apple's on-device machine learning framework. When a technician captures a photo during an inspection, the model analyzes it in seconds and highlights detected anomalies with bounding boxes and confidence scores.

// Example: MVI offline inspection result
{
  "inspectionId": "INS-2026-0720-001",
  "assetNum": "PUMP-1001",
  "photoTimestamp": "2026-07-20T14:23:11Z",
  "findings": [
    {
      "defectType": "oil_leak",
      "confidence": 0.94,
      "boundingBox": {"x": 120, "y": 340, "width": 85, "height": 60},
      "severity": "high"
    },
    {
      "defectType": "surface_corrosion",
      "confidence": 0.78,
      "boundingBox": {"x": 200, "y": 150, "width": 120, "height": 90},
      "severity": "medium"
    }
  ],
  "modelVersion": "MVI-Industrial-v2.3",
  "deviceModel": "iPad Pro 12.9",
  "processingTimeMs": 340
}

When connectivity is restored, the inspection results and annotated photos sync back to Maximo, creating inspection records with the AI-identified defects attached. This creates a permanent record of the asset condition at the time of inspection, supporting compliance audits and trend analysis.

Model Management: Administrators can configure which MVI models are available for offline use. Different models may be trained for different asset types (pumps, transformers, pipelines, structures). The mobile app downloads only the models relevant to the technician's assigned work, conserving device storage. Models are updated periodically, and the app checks for model updates during synchronization. A typical industrial MVI model is 50 to 200 MB in size, so administrators should ensure that field devices have adequate storage before deploying multiple models.

iOS Requirement: Offline visual inspection is currently available only on iOS devices. The on-device AI processing relies on Core ML, which is specific to Apple's ecosystem. Android devices can still capture photos for visual inspection, but analysis requires server connectivity. If your field organization uses a mix of iOS and Android devices, plan your visual inspection rollout accordingly. Consider standardizing on iOS for technicians who perform regular visual inspections, or ensure that Android users have connectivity when inspection is required.

QR-Code Onboarding: Faster Device Provisioning

A seemingly simple but operationally valuable feature: QR-code setup for mobile devices. In previous versions, connecting a mobile device to a specific Maximo environment required the technician to manually enter the server URL, their username, and other configuration details. This was error-prone, especially for technicians setting up a new device or switching between environments (development, staging, production).

MAS 9.2 introduces QR-code based onboarding. An administrator generates a QR code from the Mobile Administrator interface. The QR code encodes the server URL, environment details, and any required configuration parameters. The technician opens the Maximo Mobile app, scans the QR code with the device camera, and the app is configured automatically.

For organizations onboarding dozens or hundreds of technicians, this eliminates a significant support burden. Instead of walking each technician through the manual setup process, administrators can distribute the QR code via email, printed cards, or direct display during training sessions. The technician scans, logs in, and is ready to work.

Generating QR Codes: The Mobile Administrator interface allows generating QR codes per environment. You can generate separate codes for development, staging, and production environments, ensuring that technicians connect to the correct environment. The QR code can be regenerated if the server URL changes or if security tokens need rotation. Consider laminating printed QR codes for distribution at field offices, and include a short instruction card with each code explaining the scanning process.

Enhanced Mobile Dashboards and Windows Support

Two additional mobile improvements in 9.2 deserve attention:

Enhanced Mobile Dashboards: Field workers can now view assigned work orders, material pick-ups, and inspection forms in one centralized dashboard within the mobile app. Previously, technicians navigated between separate sections of the app to see their work assignments, required materials, and pending inspections. The unified dashboard surfaces all of this on a single screen, reducing navigation time and ensuring that material requirements are visible before the technician leaves for the job site.

Windows Support: Maximo Mobile is officially supported on Windows via the Microsoft Store. This is not a new feature in 9.2 but is worth highlighting because many organizations are unaware of it. Technicians who use Windows tablets or laptops in the field can install the Maximo Mobile app from the Microsoft Store rather than needing a separate iOS or Android device.

This expands the hardware options for field teams. Organizations that have standardized on Windows devices for IT reasons can use the same devices for Maximo Mobile without procuring additional tablets. The Windows app provides the same functionality as the iOS and Android versions, including offline capability and crew support.

Practical Implications

The mobile improvements in MAS 9.2 collectively transform how field teams work. Crew-based execution eliminates redundant individual actions on shared work orders. The AI assistant reduces the navigation burden for technicians, especially new ones. Offline visual inspection brings AI defect detection to remote locations. QR-code onboarding simplifies device provisioning. The unified dashboard improves daily planning. And Windows support expands hardware choices.

Rollout requires planning. Crew operations need to be enabled and configured in the Technician App configuration. MVI models need to be selected, downloaded, and assigned to relevant work types. QR codes need to be generated and distributed. Training materials need to be updated to reflect the new crew workflow and AI assistant capabilities.

Start with a pilot group of one or two crews. Enable crew operations, configure the AI assistant, and deploy MVI models for a specific asset type. Gather feedback for two to four weeks, refine the configuration, and then expand to additional crews and asset types. The phased approach reduces risk and allows your team to build confidence with the new capabilities before a full rollout.

Bottom Line

Maximo Mobile 9.2 is the release that finally brings true crew-based field execution to Maximo. Combined with AI assistant queries, offline visual inspection, simplified onboarding, and a unified dashboard, this is the most operationally impactful mobile update IBM has delivered. Organizations with field crews should prioritize enabling crew operations and the AI assistant immediately after upgrading. The productivity gains from eliminating redundant individual actions on crew work orders alone will justify the configuration effort, and the AI assistant will particularly benefit organizations with newer technicians who need guidance in the field.