AI asset data model attributes
reference australia Updated Sep 10, 2026 2 min read ai-asset-data-model-attributes.md
Additional attributes for the AI asset data model.
Attributes
AI model product model: Product Information for the AI model that is used by the AI system to generate responses without human intervention (cmdb_ai_model_product_model).
|
Attribute |
Description |
|---|---|
|
Model parameters info |
Number of parameters for the model. |
|
Supported languages |
Languages supported. |
|
Model size |
Size of the model in MB. Mostly applicable for models developed and deployed within the organization. |
|
Deployment guidelines |
Instructions applicable for models developed and deployed within the organization. |
|
Source |
Links or details of source of the model sources example: Hugging face, Microsoft, and so on. |
|
Training procedure |
Types of training- Decision Trees
|
|
Context window |
Size of input sequences that the model can handle (number of tokens). |
| Attribute | Description |
|---|---|
| Data type | Describes data, example: Text, Image, Video, and Table |
| Source | Links or details of source of the dataset sources, example: Customer, Wikipedia, Hugging face, Crowd sourced, and so on. |
| Acceptable usage | Acceptable usage of the data according to license / contract example: Training, and Evaluation. |
AI prompt product model: Product Information for instructions given to AI models to get a response for AI system (cmdb_ai_dataset_product_model).
| Attribute | Description |
|---|---|
| Documentation | Links and information about requirements, design, and related information. |
AI system product model: Product Information for software that provides ML / AI capability to generate outputs, such as decisions, recommendations, content, or predictions (cmdb_ai_system_product_model).
| Attribute | Description |
|---|---|
| Documentation | Links and information about requirements, design, and related information. |
| Attribute | Description |
|---|---|
| Data classification | Classification according to organization's data classification model, example: Public, confidential, and customer confidential. |
| Attribute | Description |
|---|---|
| ServiceNow® record reference | Reference to Now Assist record. |
| ServiceNow® table | Now Assist table. |
| Attribute | Description |
|---|---|
| AI models | Reference to more than one associated models. |
| Evaluation Dataset | Reference to more than one associated datasets used for evaluation. |
| Evaluation Metrics Report | Details of evaluation results. |
| Attribute | Description |
|---|---|
| Base model | This AI model version was derived from an internal model developed within the organization. |
| Model weights info | Additional model information if available. Mostly applicable for models developed within the organization. |
| Required infrastructure | Documentation of infrastructure requirements for model deployment, primarily for models deployed within an organization. Example: Infrastructure stack and processing requirements. |
| Training dataset | Reference to one or more associated datasets used for training the model. These datasets are mostly applicable for models developed within the organization. |
| Evaluation dataset | Reference to one or more associated datasets used for evaluating the model. These datatsets are mostly applicable for models developed within the organization. |
| Evaluation metrics report | Links or details of evaluation results |
| License details | Link or detail to applicable licenses applied to the model. |
| Model card | Links to shareable model card (Internal and external model card). |
|
Attribute |
Description |
|---|---|
|
Base datasets |
This version of the AI dataset was derived from the previous version. |
|
Dataset card |
Information on number of records, distribution, and so on.Documentation for data quality and known risks and limitations. |
|
License details |
Link or detail to applicable licenses applied to the dataset, example: CommonCore, Apache 2.0,etc. |
|
Attribute |
Description |
|---|---|
|
Prompt information |
Details of the prompt. |
|
AI model |
Reference to the AI model for which the prompt is created. |
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--- title: AI asset data model attributes description: Additional attributes for the AI asset data model. locale: en-US canonical_url: https://www.servicenow.com/docs/r/australia/intelligent-experiences/ai-control-tower/ai-asset-data-model-attributes.html release: australia product: AI Control Tower classification: ai-control-tower topic_type: reference last_updated: "2026-09-10" reading_time_minutes: 2 breadcrumb: [AI Control Tower reference \(legacy\), AI Control Tower \(legacy\), Establishing AI governance, Enable AI Experiences] --- # AI asset data model attributes Additional attributes for the AI asset data model. ## Attributes AI model product model: Product Information for the AI model that is used by the AI system to generate responses without human intervention \(cmdb\_ai\_model\_product\_model\). <table id="table_cxz_jsk_t2c"><thead><tr><th> Attribute </th><th> Description </th></tr></thead><tbody><tr><td> Model parameters info </td><td> Number of parameters for the model. </td></tr><tr><td> Supported languages </td><td> Languages supported. </td></tr><tr><td> Model size </td><td> Size of the model in MB. Mostly applicable for models developed and deployed within the organization. </td></tr><tr><td> Deployment guidelines </td><td> Instructions applicable for models developed and deployed within the organization. </td></tr><tr><td> Source </td><td> Links or details of source of the model sources example: Hugging face, Microsoft, and so on. </td></tr><tr><td> Training procedure </td><td> Types of training- Decision Trees - Deep Neural Networks - Linear Regression - Logistic Regression - Random Forest - Supervised Learning - Unsupervised Learning - Reinforcement Learning - Transfer Learning - Semi-Supervised Learning - Instruction Finetuning - Supervised Finetuning </td></tr><tr><td> Context window </td><td> Size of input sequences that the model can handle \(number of tokens\). </td></tr></tbody> </table>AI dataset product model: Product Information for the collection of data that is used to train and test AI models \(cmdb\_ai\_dataset\_product\_model\). |Attribute|Description| |---------|-----------| |Data type|Describes data, example: Text, Image, Video, and Table| |Source|Links or details of source of the dataset sources, example: Customer, Wikipedia, Hugging face, Crowd sourced, and so on.| |Acceptable usage|Acceptable usage of the data according to license / contract example: Training, and Evaluation.| AI prompt product model: Product Information for instructions given to AI models to get a response for AI system \(cmdb\_ai\_dataset\_product\_model\). |Attribute|Description| |---------|-----------| |Documentation|Links and information about requirements, design, and related information.| AI system product model: Product Information for software that provides ML / AI capability to generate outputs, such as decisions, recommendations, content, or predictions \(cmdb\_ai\_system\_product\_model\). |Attribute|Description| |---------|-----------| |Documentation|Links and information about requirements, design, and related information.| |Attribute|Description| |---------|-----------| |Data classification|Classification according to organization's data classification model, example: Public, confidential, and customer confidential.| |Attribute|Description| |---------|-----------| |ServiceNow® record reference|Reference to Now Assist record.| |ServiceNow® table|Now Assist table.| |Attribute|Description| |---------|-----------| |AI models|Reference to more than one associated models.| |Evaluation Dataset|Reference to more than one associated datasets used for evaluation.| |Evaluation Metrics Report|Details of evaluation results.| |Attribute|Description| |---------|-----------| |Base model|This AI model version was derived from an internal model developed within the organization.| |Model weights info|Additional model information if available. Mostly applicable for models developed within the organization.| |Required infrastructure|Documentation of infrastructure requirements for model deployment, primarily for models deployed within an organization. Example: Infrastructure stack and processing requirements.| |Training dataset|Reference to one or more associated datasets used for training the model. These datasets are mostly applicable for models developed within the organization.| |Evaluation dataset|Reference to one or more associated datasets used for evaluating the model. These datatsets are mostly applicable for models developed within the organization.| |Evaluation metrics report|Links or details of evaluation results| |License details|Link or detail to applicable licenses applied to the model.| |Model card|Links to shareable model card \(Internal and external model card\).| <table id="table_jqn_pzk_t2c"><thead><tr><th> Attribute </th><th> Description </th></tr></thead><tbody><tr><td> Base datasets </td><td> This version of the AI dataset was derived from the previous version. </td></tr><tr><td> Dataset card </td><td> Information on number of records, distribution, and so on.Documentation for data quality and known risks and limitations. </td></tr><tr><td> License details </td><td> Link or detail to applicable licenses applied to the dataset, example: CommonCore, Apache 2.0,etc. </td></tr></tbody> </table><table id="table_vjj_xbl_t2c"><thead><tr><th> Attribute </th><th> Description </th></tr></thead><tbody><tr><td> Prompt information </td><td> Details of the prompt. </td></tr><tr><td> AI model </td><td> Reference to the AI model for which the prompt is created. </td></tr></tbody> </table>
| title | AI asset data model attributes |
| description | Additional attributes for the AI asset data model. |
| locale | en-US |
| canonical_url | https://www.servicenow.com/docs/r/australia/intelligent-experiences/ai-control-tower/ai-asset-data-model-attributes.html |
| release | australia |
| product | AI Control Tower |
| classification | ai-control-tower |
| topic_type | reference |
| last_updated | 2026-09-10 |
| reading_time_minutes | 2 |
| breadcrumb | AI Control Tower reference \(legacy\)AI Control Tower \(legacy\)Establishing AI governanceEnable AI Experiences |