About IFS.ai Work Task Template Optimizer

IFS.ai Work Task Template Optimizer uses generative AI to recommend updates to Work Task Templates based on real reported maintenance data. Customers often struggle to maintain templates because of large volumes of reported data, inconsistencies across templates, and time-consuming manual updates that can introduce errors — and failing to capture changes such as different resource hours or materials can lead to inefficiencies, unplanned downtime, or misallocated resources. In practice, this means you can generate data-driven recommendations, review and refine them, save them, and apply them directly when creating a new template revision. Output quality depends on the quality and completeness of the reported Work Task and PM Action data.

Who This Feature Is For and Why It Matters

This feature is designed for roles involved in maintaining and revising Work Task Templates, including:

Maintenance engineers and planners responsible for keeping templates accurate
Preventive maintenance coordinators overseeing template revisions
Reliability engineers analyzing variations between planned and reported work

Use this feature when you need to:

Determine whether a Work Task Template requires revision based on reported data
Capture and store recommendations for review before applying them
Apply consistent, data-driven updates across template revisions

By using this feature, you can:

Ensure continuity of AI-generated recommendations across template revisions
Reduce manual effort and rework by using stored recommendations
Improve consistency, accuracy, and planning efficiency across resources, materials, and scheduling

Where to Find It

Access this feature from the Work Task Template page.

Page: Work Task Template

Functional Area: Preventive Maintenance

Location: The Recommendations for New Revision command at the page level, and the View AI Recommendations command under the Work List tab of preliminary and active revisions.

How the Feature Uses Data

The feature analyzes reported Work Task data within a selected date range to detect variations, trends, and anomalies that may indicate a template update is needed.

The feature uses:

Reported Work Task data, including resource hours, materials, and planning
Work Tasks created from connected PM Actions
The date range selected for AI processing

It also uses:

Current page context
The Work Task Template structure, including Work List No. and Cost Types

The feature does not use:

Data outside the selected date range
Data unavailable due to missing access or configuration

Understanding the Output

The feature generates a set of prioritized recommendations for updating the Work Task Template, ordered by Work List No. and Cost Types and covering resources, materials, and planning.

All recommendations are pre-selected by default and can be unselected, edited, or deleted before saving.
Zero recommendations may be returned if no significant variations are found in the reported data.
Saved recommendations are stored in a temporary database for use during future revisions.

Results are aligned to the reported data, so a rich set of reported Work Tasks and PM Actions yields more relevant recommendations, while sparse or limited data may return fewer or more generic results.

Enabling and Using the Feature

Prerequisites

AI Services must be enabled.
Sufficient AI tokens must be available.
A Work Task Template must exist.
Reported Work Task or PM Action data must exist within the date range to be analyzed.
For the View AI Recommendations command to appear, a preliminary or active revision must be created, a Work List must be selected, and saved recommendations must be available.

Generate

Open the Work Task Template page.
Select the Recommendations for New Revision command.
In the assistant, select the date range used to filter Work Tasks and PM Actions, and allow the system to process the data.

Review and Refine

Review the recommendations, which are ordered by Work List No. and Cost Types and pre-selected by default.
Unselect any items that are not required.
Use Regenerate Recommendations if the initial set is not suitable.
On the save page, edit or delete the selected recommendations before completing the action.

Apply

The feature does not automatically update data. You must confirm changes before they are applied. Select Finish to save the selected recommendations to the temporary database. When creating a preliminary or active revision, select a Work List and use the View AI Recommendations command to display the saved recommendations for resources, materials, and planning, and apply them directly to the revision. You can adjust the date range and regenerate recommendations to produce a new set.

Example Actions

Based on generated results, you may:

Adjust planned resource hours to match reported values
Add or update materials based on reported usage
Refine planning details on the template
Apply saved recommendations consistently across new revisions

Improving the quality and completeness of reported Work Task and PM Action data can help improve output relevance over time.

Important to Know

Generated output is a suggestion and must be reviewed before use.

The AI does not guarantee correctness or completeness.

The AI does not replace professional judgment.

Company-specific standards and terminology must be applied manually.

If no results are returned, verify that required input data is complete and that the prerequisites are met.