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

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    - australia

ft:locale :

    - en-US

ft:publication_title :

    - Australia Enable AI

ft:clusterId :

    - platai

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workflow :

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---

# Reviewing regulatory classification and compliance status

# Reviewing regulatory classification and compliance status {#ariaid-title1}

Release version: Australia  
Updated September 10, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 4 minutes to read
Summarize  
![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI  
This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete.  

## Summary of Reviewing regulatory classification and compliance status

This functionality enables ServiceNow customers to assess and monitor the regulatory risk classification and compliance posture of their AI assets, including AI systems, models, and datasets.
It provides a clear view of how these assets align with configured governance frameworks and regulatory expectations, helping governance teams, compliance officers, and AI administrators manage risk and compliance effectively.
Show full answer Show less  

## Key Features

* **Regulatory Risk Classification:** AI assets are categorized into risk levels such as Low, Medium, High, Unacceptable, Critical, or To be determined, visualized via donut charts. This classification is based on the asset's regulatory risk assessment and helps identify assets needing intervention.
* **Compliance Score:** Displays framework-specific compliance scores indicating how well AI systems conform to applicable regulations and policies. Scores are based on control attestations mapped to authority documents or policies, with options to filter and view related issues and cases.
* **Real-Time and Scheduled Updates:** Regulatory risk classifications update upon completion of assessments, while compliance scores are refreshed daily through scheduled jobs. Data is displayed live on dashboards without needing manual refreshes.
* **Entity Mapping:** AI systems are linked to entities whose compliance scores contribute to the overall system compliance score, ensuring accurate and comprehensive risk posture evaluation.
* **Exclusion of Retired/Cancelled Systems:** Only active AI systems are considered in compliance scoring to maintain focus on current assets.

## Practical Use and Customer Benefits

ServiceNow customers can leverage these insights to:

* Obtain a portfolio-wide snapshot of AI regulatory risk and compliance status.
* Prioritize risk mitigation efforts by identifying high-risk or non-compliant AI assets quickly.
* Ensure governance frameworks are effectively applied and monitor compliance against authority documents and policies.
* Maintain up-to-date regulatory and compliance data through automated processes, reducing manual effort and increasing accuracy.
* Support audit readiness and regulatory reporting with clear visualizations and detailed compliance metrics.

## Important Considerations

The authority documents provided serve as guidance and do not constitute legal advice or guarantee regulatory compliance. Customers remain responsible for ensuring adherence to applicable laws and standards in their jurisdictions. Proper entity mapping is critical for accurate compliance scoring.  
Review regulatory risk classification and compliance posture to understand how AI assets align with configured governance expectations.

## Overview of regulatory classification and compliance status {#gov-airc-regulatory-status__overview-regulatory-classification-compliance-status}

Regulatory risk classification and compliance score views help you understand how AI assets are categorized and how their control posture aligns with configured frameworks.

AI assets refer to the various components and resources that are essential for the development, deployment, and operation of artificial intelligence systems. These assets can include:

1. AI systems: The complete software or hardware infrastructure that runs AI algorithms and processes. This can include machine learning platforms, natural language processing systems, and other AI-driven applications.
2. AI models: The mathematical and computational models that are trained on data to perform specific tasks. These models can range from simple linear regression models to complex deep learning neural networks.
3. AI datasets: The collections of data used to train, validate, and test AI models.

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For more information, see [AI systems](https://www.servicenow.com/docs/access?context=ai-system-airc&version=australia&pubname=australia-governance-risk-compliance&ft:locale=en-US), [AI models](https://www.servicenow.com/docs/access?context=ai-model-airc&version=australia&pubname=australia-governance-risk-compliance&ft:locale=en-US), and [Datasets](https://www.servicenow.com/docs/access?context=dataset-airc&version=australia&pubname=australia-governance-risk-compliance&ft:locale=en-US).

At the portfolio level, you can get a snapshot view of the regulatory risk classification for your AI portfolio. This classification groups AI assets into categories such as unacceptable, high, medium, and low. Compliance views show an overall
compliance score and framework-related posture for authority documents or policies.

## Regulatory risk classification {#gov-airc-regulatory-status__regulatory-risk-classification}

The Regulatory risk classification widget presents a donut chart that organizes AI assets into risk levels based on their regulatory risk
assessment results. This section displays the risk classifications of AI systems, AI models, and datasets using donut charts. The risks are qualitatively classified as Low,
Medium, High, Unacceptable, Critical, and To be determined. The risk level displayed for each asset is
the regulatory risk classification assigned when the asset's regulatory risk classification assessment completes. This dashboard widget enables your governance teams, compliance officers, and AI administrators to assess risk
exposure and identify assets requiring intervention.

How this is calculated:{#gov-airc-regulatory-status__risk-classification-calculation}

For the full process, including the properties and records involved, see [Classifying AI assets by regulatory risk](https://www.servicenow.com/docs/LeJWku~rbfOnMP_7k9JozA "Regulatory risk classification places an AI asset in a risk rating, such as Low or High, based on the score from a risk assessment.").  
* Managed assets: The risk level shown for an asset comes from the `risk_score` field on the asset's governance details record. This field is populated when the asset's regulatory risk classification assessment completes, and the widget reflects that value in real time on every page load.
* Unmanaged assets: The risk level shown for an unmanaged asset comes from the Use \& purpose field on the asset's governance details record.

## Compliance score {#gov-airc-regulatory-status__compliance-score}

Framework-specific compliance posture and issue indicators help you understand whether governance coverage is available for the selected frameworks and which areas may
require additional attention.

Compliance scores measure how well AI systems conform to applicable regulations, policies, and controls. The section shows compliance based on controls implemented. By default, compliance
scores are displayed for the priority frameworks configured in your environment. Each framework's citations, and any child citations, are mapped to control objectives, and each citation's compliance score is calculated based
on its control attestations.

You can choose to view compliance data by selecting one of
two options: Authority documents or Policies. Additionally, you can view the overall compliance score percentage, along with the number of compliant and non-compliant authority
documents and policies, by using the drop-down filter to select specific authority documents or policies. You can also see all the issues that require immediate attention and AI cases related to each authority document or
policy.

Compliance score calculation:

For the calculation rules, an example, and how scores are processed, see [Compliance score calculation](https://www.servicenow.com/docs/5dwedZjyxoqkHEk6lFkBbw "The compliance score of an AI system measures how well its controls are met, based on the scores of its active related entities.").

1. Each AI system is linked to one or more entities or profiles through the entity map record (sn_grc_ai_gov_ai_system_entity_map).
2. Each entity has its own compliance score calculated by the Policy \& Compliance engine. The score is based on the state of its controls (whether controls pass or fail compliance tests and attestations).
3. The AI system's compliance score is calculated as the average of all active entities' compliance scores, truncated to a whole number.

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Note:  
* Compliance scores depend on linked entities; ensure all relevant entities are properly mapped to AI systems for accurate scoring.
* Retired and Cancelled AI systems are excluded from compliance score calculations to maintain focus on active systems.
* Compliance scores are averaged across all active linked entities; individual entity scores may vary.
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The authority documents are provided solely for informational and guidance purposes to assist with the initial setup of AI Risk and Compliance frameworks. It doesn't constitute legal advice or assurance of regulatory
compliance. You're solely responsible for ensuring that all use of the content complies with applicable laws, regulations, directives, and industry standards in their jurisdictions.

## How data is determined {#gov-airc-regulatory-status__section_fgt_4n4_xjc}

Regulatory status data is updated through scheduled and on-demand processes that evaluate your AI assets and calculate their risk and compliance metrics.

Regulatory risk classification data:

* The `risk_score` field on the governance details record is populated when the asset's regulatory risk classification assessment completes
* Status charts and reports are generated in real time based on live values; no scheduled refresh is required
* Widgets and visualizations reflect current data on every page load

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Compliance score data:

* Individual AI system compliance scores are calculated by scheduled and on-demand jobs
* System scores are based on the compliance scores of linked entities, which are maintained by the Policy \& Compliance engine
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## Scheduled and on-demand jobs {#gov-airc-regulatory-status__section_w2t_4n4_xjc}

Regulatory status data is kept current through the following automated processes:

For regulatory risk classification:

* No scheduled or on-demand jobs directly update risk classifications
* The `risk_score` field is populated when a regulatory risk classification assessment completes

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For compliance scores:

* AI system Compliance score calculation: Calculates individual AI system compliance scores based on linked entity scores
* AIRC daily compliance score scheduled job: Refreshes compliance score data for the home page compliance score widget on a daily schedule
{#gov-airc-regulatory-status__ul_y2t_4n4_xjc}