---
sourceDocument: Zurich Enable AI
sourceDocumentLink: https://www.servicenow.com/docs/r/zurich/intelligent-experiences

 Release :

    - zurich

ft:locale :

    - en-US

ft:publication_title :

    - Zurich Enable AI

ft:clusterId :

    - platai

bundleId :

    - platai

workflow :

    - Platform


---

# Lifecycle tasks

# AI asset lifecycle tasks {#ariaid-title1}

Release version: Zurich  
Updated April 23, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read
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![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI  
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## Summary of AI asset lifecycle tasks

AI asset lifecycle tasks enable ServiceNow customers to manage AI assets through structured governance stages by completing necessary reviews, assessments, and approvals.
These tasks ensure consistent oversight as AI assets progress from onboarding to active use and eventual retirement within the AI Control Tower.
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## How lifecycle tasks are generated and managed

* Lifecycle tasks are created by AI asset lifecycle playbooks during the Onboard and Retire stages.
* Each task corresponds to a playbook activity step requiring human judgment, such as risk evaluation, regulatory confirmation, or information collection.
* Tasks are routed to designated roles (e.g., AI steward, asset owner) based on playbook logic.
* The asset cannot move to the next activity or lifecycle stage until all required tasks in the current stage are completed, enforcing strict governance.

## Lifecycle stages

* **Onboard:** Introduction of the asset into the organization, using a playbook with activities like Assess, Build and test, and Deploy. Each activity generates corresponding lifecycle tasks.
* **Maintain:** Active use phase after onboarding completion. This stage does not generate lifecycle tasks but tracks change requests instead.
* **Retire:** Decommissioning phase with its own playbook to generate tasks necessary for retiring the asset.

## Where lifecycle tasks appear in AI Control Tower

* **Top action items widget:** Displays lifecycle tasks assigned to you on the Home page.
* **Activity Center:** Tasks are shown on the Lifecycle tasks sub-tab under Team, Assigned to you, and Unassigned views.
* **Lifecycle tab on asset records:** Displays lifecycle tasks in the playbook visualization, showing each task's role in the asset's lifecycle progression.

These capabilities help ServiceNow customers maintain rigorous governance over AI assets by breaking down complex oversight into manageable, role-based tasks integrated within the AI Control Tower platform.  
Advance managed AI assets through controlled stages of governance by completing
the reviews, assessments, and approvals that AI asset lifecycle playbooks require.

A lifecycle task is a unit of governance work that an AI asset lifecycle playbook generates and assigns to an AI steward, asset owner, or other reviewer. Each lifecycle task corresponds to a step in a playbook activity that
requires human judgment, such as evaluating an asset's risk, confirming its regulatory conformity, or collecting the information a review requires. AI Control Tower uses lifecycle tasks to help enforce consistent governance as a
managed AI asset moves from onboarding through active use to retirement.

## How lifecycle tasks are generated {#ac-ai-asset-lifecycle-tasks__origin}

Lifecycle tasks are generated by the playbooks that run during the Onboard and
Retire stages. Each playbook advances the asset through its own set of named
activities and generates the tasks required to complete each one. For example,
the Onboarding playbook's Assess activity might generate an impact assessment
task, a legal collaboration task, a security clearance collaboration task, and an
architecture review task.

AI Control Tower routes each task to the role responsible for completing it, based
on the playbook's logic. The asset cannot advance to the next activity or
lifecycle stage until all required tasks for the current activity are
completed.

## Lifecycle stages {#ac-ai-asset-lifecycle-tasks__stages}

Every managed AI asset progresses through three lifecycle stages, shown as a
horizontal progress indicator on the asset's Lifecycle
tab. AI Control Tower generates lifecycle tasks in the two stages that run a
playbook:

Onboard
:   The asset is introduced into the organization. The Onboarding playbook
    advances the asset through its own activities, including Assess, Build
    and test, and Deploy, and generates a lifecycle task for each activity it
    requires.

Maintain
:   The asset is in active, ongoing use. This stage becomes available after
    onboarding is complete. It does not run a playbook, so it tracks change
    requests instead of lifecycle tasks.

Retire
:   The asset is decommissioned and removed from active use. This stage
    becomes available after onboarding is complete and runs its own playbook
    to generate the lifecycle tasks required to retire the asset.

## Where lifecycle tasks appear {#ac-ai-asset-lifecycle-tasks__where-they-appear}

Lifecycle tasks appear in three places in AI Control Tower:

The Top action items widget on the Home page
:   Lifecycle tasks assigned to you appear on the Assigned to you tab. Lifecycle tasks with no assignee appear on the
    Unassigned tab.

Activity Center
:   Lifecycle tasks appear on the Lifecycle tasks
    sub-tab of the Team, Assigned to you, and Unassigned views,
    depending on assignment.

The Lifecycle tab on an asset record
:   Lifecycle tasks for a specific asset appear in the playbook visualization
    on the Lifecycle tab, where you can see how each
    task fits into the asset's overall lifecycle progression.