---
sourceDocument: Yokohama Enable AI
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/yokohama/intelligent-experiences

 Release :

    - yokohama

ft:locale :

    - en-US

ft:publication_title :

    - Yokohama Enable AI

ft:clusterId :

    - platai

bundleId :

    - platai

workflow :

    - Platform


---

# Inter-dependencies

# Inter-dependencies {#ariaid-title1}

Release version: Yokohama  
Updated August 25, 2025  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 1 minute to read  
Explore the inter-dependencies of AI systems, AI models, and datasets.

An AI system operates as part of a larger framework, closely connected to the AI model powering its capabilities and the datasets that shape its behavior. While these elements are interrelated, each plays a unique role and should be
clearly identified to confirm effective governance.

Overlooking any aspect, such as the training dataset or the model supporting an AI feature can result in incomplete risk assessments, audit challenges, or compliance issues.

Comprehensive responsible AI governance requires attention to all these components:

* Inventory for each AI system
* Identify the associated AI model
* Document the dataset

{#understanding-interdependencies__ul_xld_nvt_kgc}

For a visual example of how these elements interact, see [Example of an AI system](https://servicenow-prod.fluidtopics.net/7D5a6ZolvcjdLtqSPV60Yw "The AI Control Tower application and the AI Risk and Compliance application play a critical role in managing and governing the responsible use of AI systems, especially in high-stakes domains such as banking and finance.")

For information on Model asset classes, see [Model asset classes](https://www.servicenow.com/docs/access?context=enterprise-model-asset-classes-app&version=yokohama&pubname=yokohama-it-asset-management&ft:locale=en-US#d396350e744)

For information on AI assets API, see AI Assets API