---
sourceDocument: Store Version History Release Notes
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/store-release-notes

 Release :

    - store

ft:locale :

    - en-US

ft:publication_title :

    - Store Version History Release Notes

ft:clusterId :

    - rnst

bundleId :

    - rnst


---

# Field Service Management Intelligent Task Recommendations release notes

# Field Service Management Intelligent Task Recommendations release notes {#ariaid-title1}

Release version: Store  
Updated September 10, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 1 minute to read  
Version history for the ServiceNow®
Field Service Management Intelligent Task Recommendations application on the ServiceNow Store.
Important:  
For details on system requirements and family compatibility, view the application listing on the [ServiceNow Store](https://store.servicenow.com/sn_appstore_store.do#!/store/home) website.

Version 30.0.5 - September 2026
:   There are no new user-facing features or enhancements in this release. The work in this version modernizes the application's underlying technical framework of fluent SDK and dependency versions to keep the app aligned with current
    platform standards, with no impact in functional behavior.

Version 29.1.0 - June 2026
:   New: Intelligent Task Recommendation now supports territory-based workflows. Dispatchers and agents can receive task recommendations based on territory assignments, in addition to existing assignment group logic. Territory demand
    channel mappings are honored, ensuring only tasks matching an agent's mapped demand channels are recommended to fill schedule gaps. Recommendations respect agent-level and multi-territory demand channel assignments, and demand
    channel filtering is consistently applied in both Dispatcher Workspace and the Agent mobile app. Task ranking is performed after demand channel filtering.

Version 29.0.6 - March 2026
:
    * Task Assignment Recommendations helps dispatchers match technicians to work orders based on the factors that actually determine whether a job gets done right --- distance, travel time, parts availability, schedule fit, and mobile capability.
    * Without it, dispatchers rely on tribal knowledge and manual checks to make assignment calls that should be data-driven. With it, the system surfaces recommended assignments based on configurable criteria, so dispatchers spend less time figuring out who to send and more time handling exceptions.
    * The recommendation engine is built specifically for field service --- not a generic task routing framework --- which means the criteria it uses reflect real operational constraints, not abstract matching logic.
    {#store-rn-fsm-intelligent-task-recommendations__ul_evd_lqx_l3c}