AI Command Center operating model

Updated: May 8, 2026

Note The content in this topic is nearly identical to the AI Governance operating model content. The only difference is the product name; this topic refers to AI Command Center.

Asset type	Description	Public ID
AI Agent	An autonomous system that perceives its environment, makes decisions based on predefined rules or learned patterns, and takes actions to achieve specific goals.	AIAgent
AI Agent Tool	A service accessible to an AI agent that automates tasks, generates content, or delivers intelligent insights.	AIAgentTool
AI Agent Version	A specific implementation of an AI agent at a point in time, capturing details like the tools, models, and configurations used.	AIAgentVersion
AI Base Model	The foundational business concept that defines the model's purpose and governing principles, remaining constant across all technical iterations. Important This asset type is currently only available for the Azure AI Foundry integration. It will become available for other AI model integrations in future versions of Collibra.	FoundationalAIModel
AI Endpoint	The access point for external systems that provides a consistent interface while allowing for the seamless exchange of underlying deployments.	AIEndpoint
AI Model Deployment	The operational instance where a model version is assigned computational resources to execute and generate real-time outputs.	AIModelDeployment
AI Model Version	A specific, immutable implementation of the model logic and parameters that serves as the audited "raw" model version before it is activated.	DeployedAIModel
AI Monitor	The configuration of automated tracking parameters and alerting thresholds used to observe a deployment’s real-world performance and detect deviations from expected behavior.	AIMonitor
AI Project	A structured initiative that involves the development, deployment, and management of AI Models and Agents.	AIProject
AI Use Case	A specific application of artificial intelligence (AI) and AI Models trained on specific data in order to solve a business problem and deliver business value. Implementing an AI Use Case may result in automating a task, improve decision-making or develop new products and services.	AIUseCase
Inference Data (asset type group)	Groups all types of assets that can be used as inference data in the context of AI Model Deployments. By default, includes the following asset types: Table (and child asset types) Storage Container (and child asset types) File	InferenceData
Output Data (asset type group)	Groups all types of assets that can hold the output generated by AI Model Deployments. By default, includes the following asset types: Table (and child asset types) Storage Container (and child asset types) File	OutputData

Other important asset types that are not specific to AI Command Center include the following:

File: Assets that represent dataset files used to fine-tune AI model versions.
Storage Container: Assets that represent the folders containing dataset files

The following image shows the relations between the AI Command Center asset types and other relevant asset types. For instructions on how to create this diagram view in your Collibra environment, see the section "Create an operating model diagram view", at the bottom of this topic.

Descriptions, attributes, and relation types

Click the relevant tab below to see descriptions and the out-of-the-box attributes, relation types and more, for each asset type.

The details relevant to each asset type apply also to their respective child asset types.

Description

An autonomous system that perceives its environment, makes decisions based on predefined rules or learned patterns, and takes actions to achieve specific goals.

Relation types

Relation type	Head role / corole tail	Public ID	Kind
is used by AI Use Case	AI Use Case uses / is used by AI Agent	AIUseCaseUsesAIAgent	Explicit
uses AI Model Version	AI Agent uses / is used by AI Model Version	AIAgentUsesAIModel	Explicit
uses AI Agent	AI Agent uses / is used by AI Agent	AIAgentUsesAIAgent	Explicit
is used by AI Agent	AI Agent uses / is used by AI Agent	AIAgentUsesAIAgent	Explicit
has version AI Agent Version	AI Agent has version / is version of AI Agent Version	AgentHasVersion	Explicit
has agent config stored in Storage Container	AI Agent has agent config stored in / contains config files for Storage Container	AIAgentContainsFileContainer	Explicit

Attributes

Attribute	Description	Public ID
AI Trust Score	Average governance maturity, safety, and operational health of your AI assets.	AITrustScore
Creation Date in Source	The date on which the resource was created in the source system.	CreationDateInSource
Description	The description of the asset. This is typically a more verbose way to describe what the asset means.	Description
Description from source system	The description from the source system of the asset.	DescriptionFromSourceSystem
Instructions	A set of guidelines, rules, or commands that define how an AI model, agent, or assistant should behave or respond.	Instructions
Tool Usage	Indicates which tools or skills the agent is allowed to use.	ToolUsage

Domain type

AI Agent assets can be created in domains of type Technology Asset Domain.

Asset statuses

By default, the Lifecycle management feature is switched on for this asset type. This allows you, in part, to configure the asset status progression for core and retirement phases of the asset lifecycle.

Phase	Asset status	Description
Core phase	Candidate	The asset is in an initial drafting state.
	Under Review	The stakeholders are reviewing an asset. The reviewer is analyzing an issue and proposing a solution.
	Accepted	The stewards approved an asset definition. The technical stewards are granting the requested access. The reviewer is appointing an assignee to resolve an issue.
Retirement phase	Rejected	You can use this status for projects that have been canceled or aren’t being considered for future production. They're in storage for future reference.
	Archived	You can use this status for projects that have been closed and are no longer in production. They are in storage for future reference.
	Missing from source	The asset is no longer available in the source.

Tip For information on editing the status of an asset, go to Edit an asset.

Description

A service accessible to an AI agent that automates tasks, generates content, or delivers intelligent insights.

Relation types

Relation type	Head role / corole tail	Public ID	Kind
can be called by AI Agent Tool	AI Agent Version can call / can be called by AI Agent Tool	AgentVersionCallsTool	Explicit
delegates to AI Agent Version	AI Agent Tool delegates to / can receive requests from AI Agent Version	AIAgentToolCallsAIAgentVersion	Explicit
delegates to AI Endpoint	AI Agent Tool delegates to / can receive requests from AI Endpoint	AIAgentToolCallsAIAgentEndpoint	Explicit
can consult data source Inference Data	AI Agent Tool can consult data source / can be consulted via Inference Data	AIAgentToolCanReadInferenceData	Explicit
can manipulate data in Output Data	AI Agent Tool can manipulate data in / can be manipulated via Output Data	AIAgentToolCanManipulateOutputData	Explicit

Attribute types

Attribute type	Description	Public ID
Description	The description of the asset. This is typically a more verbose way to describe what the asset means.	Description

Domain type

AI Agent Tool assets can be created in domains of type Technology Asset Domain.

Asset statuses

Asset status	Description
Candidate	The asset is in an initial drafting state.
Under Review	The stakeholders are reviewing an asset.
Accepted	The stewards approved an asset definition.
Rejected	You can use this status for projects that have been canceled or aren’t being considered for future production. They're in storage for future reference.
Archived	You can use this status for projects that have been closed and are no longer in production. They are in storage for future reference.
Missing from source	The asset is no longer available in the source.

This asset type is not eligible for the Lifecycle management feature.

Tip For information on editing the status of an asset, go to Edit an asset.

Description

A specific implementation of an AI agent at a point in time, capturing details like the tools, models, and configurations used.

Relation types

Relation type	Head role / corole tail	Public ID	Kind
is version of AI Agent	AI Agent has version / is version of AI Agent Version	AgentHasVersion	Explicit
infers using LLM AI Endpoint	AI Agent Version infers using LLM / is used for inference of AI Endpoint	AgentVersionInvokesModelEndpoint	Explicit
can call AI Agent Tool	AI Agent Version can call / can be called by AI Agent Tool	AgentVersionCallsTool	Explicit
can receive requests from AI Agent Tool	AI Agent Tool delegates to / can receive requests from AI Agent Version	AIAgentToolCallsAIAgentVersion	Explicit

Complex relation types

Name	Description	Relation types	Attribute types	Public ID	System-managed
AI Agent Deployment	Represents the deployment of a specific AI agent version to an AI endpoint, capturing operational details such as traffic allocation. A single agent version may have multiple deployments across different endpoints, and an endpoint may expose multiple agent deployments simultaneously	is deployment of - AI Agent Version (1:1) is exposed on - AI Endpoint (1:1) is monitored by - AI Monitor (0:n)	Traffic Split Percentage (1:1)	AIAgentDeployment

Attribute types

Attribute type	Description	Public ID
AI Trust Score	Average governance maturity, safety, and operational health of your AI assets.	AITrustScore
Version	A label or identifier that represents a specific state or iteration, used to track changes over time.	Version
Creation Date in Source	The date on which the resource was created in the source system.	CreationDateInSource
Description from source system	The description from the source system of the asset.	DescriptionFromSourceSystem
Instructions	A set of guidelines, rules, or commands that define how an AI model, agent, or assistant should behave or respond.	Instructions
Owner in Source	The owner(s) of the corresponding object in the data source.	Version

Domain type

AI Agent Version assets can be created in domains of type Technology Asset Domain.

Asset statuses

Phase	Asset status	Description
Core phase	Candidate	The asset is in an initial drafting state.
	Under Review	The stakeholders are reviewing an asset. The reviewer is analyzing an issue and proposing a solution.
	Accepted	The stewards approved an asset definition. The technical stewards are granting the requested access. The reviewer is appointing an assignee to resolve an issue.
Retirement phase	Rejected	You can use this status for projects that have been canceled or aren't being considered for future production. They're in storage for future reference.
	Archived	You can use this status for projects that have been closed and are no longer in production. They are in storage for future reference.
	Missing from source	The asset is no longer available in the source.

Tip For information on editing the status of an asset, go to Edit an asset.

Important This asset type is currently only available for the Azure AI Foundry integration. It will become available for other AI model integrations in future versions of Collibra.

Description

The foundational business concept that defines the model's purpose and governing principles, remaining constant across all technical iterations.

Relation types

Relation type	Head role / corole tail	Public ID	Kind
uses AI Base Model	AI Base Model uses / is used by AI Base Model	FoundationalAIModelUsesFoundationalAIModel	Explicit
is used by AI Base Model	AI Base Model uses / is used by AI Base Model	FoundationalAIModelUsesFoundationalAIModel	Explicit
complies to Governance Asset	Asset (AI Base Model) complies to / applies to Governance Asset (Policy)	AssetCompliesToGovernanceAsset	Explicit
has version AI Model Version	AI Base Model has version / is version of AI Model Version	ModelHasVersion	Explicit
used in AI Use Case	AI Use Case uses / used in AI Base Model	AIUseCaseUsesBaseModel	Explicit
is provided by Vendor	AI Base Model is provided by / provides Vendor	BaseModelProvidedByVendor	Explicit

Attribute types

Attribute type	Description	Public ID
AI Trust Score	Average governance maturity, safety, and operational health of your AI assets.	AITrustScore
Creation Date in Source	The date on which the resource was created in the source system.	CreationDateInSource
Description	The description of the asset. This is typically a more verbose way to describe what the asset means.	Description
Description from source system	The description from the source system of the asset.	DescriptionFromSourceSystem
Owner in Source	The owner(s) of the corresponding object in the data source.	OwnerInSource
Required Content Filtering	Defines the criteria or rules that need to be applied to restrict, refine, or control the type of content generated by an AI Model.	RequiredContentFilter
Retirement Date in Source	The date on which the resource was retired in the source system.	RetirementDateInSource
Retrain Cycle	The frequency at which the asset is retrained.	RetrainCycle

Domain type

AI Base Model assets can be created in domains of type Technology Asset Domain.

Asset statuses

Asset status	Description
Candidate	The asset is in an initial drafting state.
Under Review	The stakeholders are reviewing an asset.
Accepted	The stewards approved an asset definition.
Rejected	You can use this status for projects that have been canceled or aren’t being considered for future production. They're in storage for future reference.
Archived	You can use this status for projects that have been closed and are no longer in production. They are in storage for future reference.
Missing from source	The asset is no longer available in the source.

This asset type is eligible for the Lifecycle management feature, but it is disabled by default.

Tip For information on editing the status of an asset, go to Edit an asset.

Description

The access point for external systems that provides a consistent interface while allowing for the seamless exchange of underlying deployments.

Relation types

Relation type	Head role / corole tail	Public ID	Kind
exposes AI Model Deployment	AI Model Deployment is exposed through / exposes AI Endpoint	DeploymentsExposedThroughEndpoint	Explicit
is used for inference of AI Agent Version	AI Agent Version infers using LLM / is used for inference of AI Endpoint	AgentVersionInvokesModelEndpoint	Explicit
can receive requests from AI Agent Tool	AI Agent Tool delegates to / can receive requests from AI Endpoint	AIAgentToolCallsAIAgentEndpoint	Explicit

Complex relation types

Name	Description	Relation types	Attribute types	Public ID	System-managed
AI Agent Deployment	Represents the deployment of a specific AI agent version to an AI endpoint, capturing operational details such as traffic allocation. A single agent version may have multiple deployments across different endpoints, and an endpoint may expose multiple agent deployments simultaneously	is deployment of - AI Agent Version (1:1) is exposed on - AI Endpoint (1:1) is monitored by - AI Monitor (0:n)	Traffic Split Percentage (1:1)	AIAgentDeployment

Attribute types

Attribute type	Description	Public ID
Access Instructions	Instructions on how to access the data.	AccessInstructions
Access Method	Indicates what method can be used to access the data.	AccessMethod
Endpoint Availability	Controls how the model endpoint is deployed and billed: Online is always-on, scales dynamically and responds synchronously. Serverless auto-scales on demand with no setup, but may have cold-start delays. Provisioned Throughput reserves fixed capacity for predictable, high-volume workloads where stable latency matters. Batch Processing processes large jobs asynchronously in bulk, good for pipelines and bulk analysis. Asynchronous queues individual requests non-blocking and returns results via callback or polling - suited for large payloads and long-running tasks. Developer/Experimental is a low-cost option with no SLA, intended for testing and fine-tune evaluation only.	EndpointAvailability
Supported Interaction Protocols	Lists the interaction protocols supported by this endpoint: REST / HTTP: Stateless HTTP. Universal and simple. gRPC: HTTP/2 + Protocol Buffers. Fast, typed, streaming. MCP: JSON-RPC over stdio or SSE. The standard for agent-to-tool connectivity. A2A: Peer-to-peer task delegation via Agent Cards over HTTP/SSE. Enterprise-scale orchestration. ACP: REST client-server with multimodal MIME messages. Now merged into A2A. ANP: Decentralized, DID-based discovery for cross-org agent collaboration on the open internet. LMOS: Three-layer (identity, transport, application) internet-scale agent protocol. AG-UI: Streams typed events from agent backend to frontend. Structured semantics for agent-user interaction. A2UI: Declarative UI spec describing what the agent wants the client to render. Carried over AG-UI.	SupportedInteractionProtocols
Traffic Split	Reflects how the traffic that is sent to an endpoint is split between different deployments.	TrafficSplit

Domain type

AI Endpoint assets can be created in domains of type Technology Asset Domain.

Asset statuses

Asset status	Description
In Use	The asset is actively being used.
Obsolete	The asset is no longer in use.
Missing from source	The asset is no longer available in the source.

This asset type is not eligible for the Lifecycle management feature.

Tip For information on editing the status of an asset, go to Edit an asset.

Description

The operational instance where a model version is assigned computational resources to execute and generate real-time outputs.

Relation types

Relation type	Head role / corole tail	Public ID	Kind
is deployment of AI Model Version	AI Model Version is deployed by / is deployment of AI Model Deployment	ModelVersionIsDeployedByModelDeployment	Explicit
uses Inference Data	AI Model Deployment uses / is used by Inference Data	ModelDeploymentInfersFromInferenceData	Explicit
produces Output Data	AI Model Deployment produces / is produced by Output Data	ModelDeploymentToOutputData	Explicit
is exposed through AI Endpoint	AI Model Deployment is exposed through / exposes AI Endpoint	DeploymentsExposedThroughEndpoint	Explicit
is monitored by AI Monitor	AI Model Deployment is monitored by / monitors AI Monitor	DeploymentMonitoredByAIMonitor	Explicit

Attribute types

Attribute type	Description	Public ID
Compute Configuration	Shows the capacity and amount of resources allocated to this asset.	ComputeConfiguration
Creation Date In Source	The date on which the resource was created in the source system.	CreationDateInSource
Description From Source System	The description from the source system of the asset.	DescriptionFromSourceSystem
Implemented Content Filtering	List the content filters activated on an AI Model deployment, to avoid unwanted output being generated.	ImplementedContentFiltering
Initiating User In Source	Shows the name of the user who initiated the creation of this resouce in the source system. We capture this as an attribute and not via responsibilities because the user who has an account in the source system may not have a Collibra user.	InitiatingUserInSource
Modification Date In Source	The date on which the resource was modified in the source system.	ModificationDateInSource
Retirement Date In Source	The date on which the resource was retired in the source system.	RetirementDateInSource

Domain type

AI Model Deployment assets can be created in domains of type Technology Asset Domain.

Asset statuses

Asset status	Description
In Use	The asset is actively being used.
Obsolete	The asset is no longer in use.
Missing from source	The asset is no longer available in the source.

This asset type is not eligible for the Lifecycle management feature.

Tip For information on editing the status of an asset, go to Edit an asset.

Description

A specific, immutable implementation of the model logic and parameters that serves as the audited "raw" model version before it is activated.

Relation types

Relation type	Head role / corole tail	Public ID	Kind
used in AI Use Case	AI Use Case uses / used in AI Model Version	AIUseCaseUsesAIModel	Explicit
trained by Asset	AI Model Version trained by / trains Asset	AIModelTrainedByAsset	Explicit
infers from Asset	AI Model Version infers from / used to infer Asset	AIModelInfersFromAsset	Explicit
has output Asset	AI Model Version has output / provides Asset	AIModelHasOutputAsset	Explicit
is provided by Vendor	AI Model Version is provided by / provides Vendor	AIModelProvidedByVendor	Explicit
uses AI Model Version	AI Model Version uses / is used by AI Model Version	AIModelUsesAIModel	Explicit
is used by AI Model Version	AI Model Version uses / is used by AI Model Version	AIModelUsesAIModel	Explicit
complies to Governance Asset	AI Model Version complies to / applies to Governance Asset (Policy)	AssetCompliesToGovernanceAsset	Explicit
is used by AI Agent	AI Agent uses / is used by AI Model Version	AIAgentUsesAIModel	Explicit
is deployed in AI Project	AI Model Version is deployed in / deploys AI Project	AIProjectDeploysAIModel	Explicit
has model files stored in Storage Container	AI Model Version has model files stored in / contains model files for Storage Container	AIModelContainsFileContainer	Explicit
is deployed by AI Model Deployment	AI Model Version is deployed by / is deployment of AI Model Deployment	ModelVersionIsDeployedByModelDeployment	Explicit
is version of AI Base Model	AI Base Model has version / is version of AI Model Version	ModelHasVersion	Explicit

Attribute types

Attribute type	Description	Public ID
AI Trust Score	Average governance maturity, safety, and operational health of your AI assets.	AITrustScore
Description	The description of the asset. This is typically a more verbose way to describe what the asset means.	Description
Model Accuracy	Model Accuracy refers to how well the model performs on a given task. Typically, this is defined by the proportion of correct predications made by the model. For example, if a model is used to classify emails as spam or not spam, and it classifies 90% of emails correctly, then the model accuracy is 90%.	ModelAccuracy
Model Precision	Model Precision refers to how accurate positive model predictions are. Typically, this is defined as the proportion of predictions that are correct. For example, if a model is used to classify emails as spam, and it correctly classifies 95% of emails as spam, then the model has a precision of 0.95.	ModelPrecision
Mean Squared Error	Mean Squared Error (MSE) refers to a model quality metric that measures the quality of the model’s predications.	MeanSquaredError
Mean Absolute Error	Mean Absolute Error (MAE) refers to a model quality metric that evaluates the performance of regression models.	MeanAbsoluteError
Model Type	Type of AI model. Values include: Generative AI, Classification, Regression, Computer Vision, Reinforcement Learning, and Image Classification.	ModelType
Feature Importance	Feature Importance refers to how important a feature is to a machine learning model. It helps you to understand which features contribute the most to the model’s predictions.	FeatureImportance
Version	If this asset is versioned (manually or in an external system), this string represents the asset version.	Version
Description from source system	The description from the source system of the asset.	DescriptionFromSourceSystem
Repository	Reference to the repository where the code behind the model is stored.	Repository
Required Content Filtering	Defines the criteria or rules that need to be applied to restrict, refine, or control the type of content generated by an AI Model.	ContentFilter
Supported Input Modalities	Specifies the fundamental types of input data the model can accept. This includes discrete categories such as text, image, audio, video, or tabular data. For multi-modal models, this attribute defines the valid combinations of these inputs (for example, text and image for a visual question answering model).	SupportedInputModalities
Supported Output Modalities	Specifies the fundamental types of output data the model can generate. This includes discrete categories such as text, image, audio, video, or tabular data. For multi-modal models, this attribute defines the valid combinations of these inputs (for example, text and image for a visual question answering model).	SupportedOutputModalities
Supported Model Customizations	Defines the available pathways for adapting the model's base capabilities to specific use cases. This attribute details the supported adaptation techniques (such as Full Fine-Tuning, Parameter-Efficient Fine-Tuning (PEFT), or Distillation) and the degree of structural flexibility allowed (for example, modular adapters or freezing specific layers). It serves as a guide for developers to understand the trade-offs between computational cost and model specialization.	SupportedModelCustomizations
Framework	The machine learning framework used to build the model.	Framework

Domain type

AI Model Version assets can be created in domains of type Technology Asset Domain.

Asset statuses

Phase	Asset status	Description
Core phase	Candidate	The asset is in an initial drafting state.
	Under Review	The stakeholders are reviewing an asset. The reviewer is analyzing an issue and proposing a solution.
	Accepted	The stewards approved an asset definition. The technical stewards are granting the requested access. The reviewer is appointing an assignee to resolve an issue.
Retirement phase	Archived	You can use this status for projects that have been closed and are no longer in production. They are in storage for future reference.
	Rejected	You can use this status for projects that have been canceled or aren’t being considered for future production. They are in storage for future reference.
	Missing from source	The asset is no longer available in the source.

Tip For information on editing the status of an asset, go to Edit an asset.

Description

The configuration of automated tracking parameters and alerting thresholds used to observe a deployment’s real-world performance and detect deviations from expected behavior.

Relation types

Relation type	Head role / corole tail	Public ID	Kind
monitors AI Model Deployment	AI Model Deployment is monitored by / monitors AI Monitor	DeploymentMonitoredByAIMonitor	Explicit

Complex relation types

Name	Description	Relation types	Attribute types	Public ID	System-managed
AI Agent Deployment	Represents the deployment of a specific AI agent version to an AI endpoint, capturing operational details such as traffic allocation. A single agent version may have multiple deployments across different endpoints, and an endpoint may expose multiple agent deployments simultaneously	is deployment of - AI Agent Version (1:1) is exposed on - AI Endpoint (1:1) is monitored by - AI Monitor (0:n)	Traffic Split Percentage (1:1)	AIAgentDeployment

Attribute types

Attribute type	Description	Public ID
Data Drift Detection Enabled	Data drift detection monitors shifts in input data distributions over time to identify when a model’s environment no longer matches its training data. This attribute type captures whether data drift detection is enabled on the AI Monitor.	DataDriftDetection
Prediction Drift Detection Enabled	Tracks changes in the model’s output distribution to identify shifts in prediction patterns, serving as an early warning for model decay when actual outcomes are delayed. This attribute type captures if whether prediction drift detection is enabled on the AI Monitor.	PredictionDriftDetection
Schedule	Defines the frequency (e.g., hourly, daily) at which a monitor analyzes data or a job is executed.	Schedule
Alert Configuration	Defines the threshold conditions that trigger an alert and the communication channels (for example email and Slack) used to notify stakeholders.	AlertConfiguration
URL	Uniform Resource Locator, also colloquially known as web address.	Url

Domain type

AI Monitor assets can be created in domains of type Governance Asset Domain.

Asset statuses

Asset status	Description
In Use	The asset is actively being used.
Obsolete	The asset is no longer in use.
Missing from source	The asset is no longer available in the source.

This asset type is not eligible for the Lifecycle management feature.

Tip For information on editing the status of an asset, go to Edit an asset.

Description

A structured initiative that involves the development, deployment, and management of AI Models and Agents.

Relation types

Relation type	Head role / corole tail	Public ID
is used by AI Use Case	AI Use Case uses / is used by AI Project	AIUseCaseUsesAIProject
deploys AI Model Version	AI Project deploys / is deployed by AI Model Version	AIProjectDeploysAIModel

Attribute types

Attribute type	Description	Public ID
Description	The description of the asset. This is typically a more verbose way to describe what the asset means.	Description
Location	The location where the actual asset is stored or can be found.	Location
Project Id	A globally unique identifier for your project.	ProjectId
URL	Uniform Resource Locator, also colloquially known as web address.	Url

Domain type

AI Project assets can be created in domains of type Technology Asset Domain.

Asset statuses

Asset status	Description
Candidate	The asset is in an initial drafting state.
Under Review	The stakeholders are reviewing an asset.
Accepted	The stewards approved an asset definition.
Archived	You can use this status for projects that have been closed and are no longer in production. They are in storage for future reference.
Rejected	You can use this status for projects that have been canceled or aren’t being considered for future production. They're in storage for future reference.

This asset type is not eligible for the Lifecycle management feature.

Tip For information on editing the status of an asset, go to Edit an asset.

Description

A specific application of artificial intelligence (AI) and AI Models trained on specific data in order to solve a business problem and deliver business value. Implementing an AI Use Case may result in automating a task, improve decision-making or develop new products and services.

Relation types

Relation type	Head role / corole tail	Public ID	Kind
is assessed by Assessment Review	Asset is assessed by / assesses Assessment Review	AssetIsAssessedByAssessmentReview	Explicit
uses AI Model Version	AI Use Case uses / used in AI Model Version	AIUseCaseUsesAIModel	Explicit
infers from Asset	AI Use Case infers from / used to infer Asset	AIUseCaseTransformsAsset	Explicit
trained by Asset	AI Use Case trained by / trains in Asset	AIUseCaseTrainedByAsset	Explicit
has output Asset	AI Use Case has output / is output Asset	AIUseCaseHasOutputAsset	Explicit
complies to Governance Asset	Asset complies to / applies to Governance Asset (Policy)	AssetCompliesToGovernanceAsset	Explicit
uses AI Agent	AI Use Case uses / is used by AI Agent	AIUseCaseUsesAIAgent	Explicit
uses AI Project	AI Use Case uses / is used by AI Project	AIUseCaseUsesAIProject	Explicit
uses AI Base Model	AI Use Case uses / used in AI Base Model	AIUseCaseUsesBaseModel	Explicit

Attribute types

Attribute type	Description	Public ID
AI Trust Score	Average governance maturity, safety, and operational health of your AI assets.	AITrustScore
Description	General description of the Use Case and its potential for the use of AI.	Description
Use Case Application	Indicates that the AI use case will be used by an external audience or internally by your organization.	UseCaseApplication
Business Case	Refers to the business problem you want to solve with the AI use case. It focuses on describing a concrete business problem. For example, I'm a customer support manager and my team receives too many support tickets.	BusinessCase
Business Value	Refers to how this AI use case can improve your organization. For example, reduce support tickets, bring in additional revenue, or mitigate risks.	BusinessValue
Business Sponsor	Refers to the Business Owner or Executive Sponsor of the AI Use Case in your organization.	BusinessSponsor
Maintenance Cost	Indicates the overall expected cost of running the Use Case over selected period of time.	MaintenanceCost
General Purpose AI	Refers to whether the model used in your AI use case is using a General Purpose AI (GPAI). Some regulatory frameworks may impose additional transparency and risk mitigation requirements for GPAI based systems, sometimes referred to as foundation models. For example, large language models (LLMs).	GeneralPurposeAI
Third Party Model	Refers to the vendor of your AI model(s) and what kind of model you are using. For example, Google Vertex.	ThirdPartyModel
Internal Model	Refers to the existing or upcoming internally built model(s) your AI use case may use.	InternalModel
Training Data Description	The training or re-retraining data used to teach the AI model(s).	TrainingDataDescription
Inference Data Description	An explanation of the input or inference data the AI model(s) uses to create output data. For example, an image classification model uses images as input data and a language model uses text as input data.	InferenceDataDescription
Model Output	An explanation of the output data that the AI model(s) is expected to create. For example, classification labels, descriptions, or complex probability predictions.	ModelOutput
Data Storage	Refers to whether any data is stored, and if so, where and how the data is stored. For example, the prompts data is stored on the cloud.	DataStorage
Automation Level	The nature and degree of automation of the AI use case. For example, are decisions going to be based solely on the automated output, or is human oversight possible or planned?	AutomationLevel
Model Monitoring	Refers to how your organization will ensure the AI model is meeting accuracy and performance expectations.	ModelMonitoring
Legal Approval Date	Date your legal team approved or rejected the AI use case.	LegalApprovalDate
Legal Approval Renewal Date	Date of the expected periodical review of the Use Case’s approval.	LegalApprovalRenewalDate
Legal Description of Model	Description of the AI model provided by your legal team. This may include any legal repercussions of processing the AI model within the context of the AI use case.	LegalModelDescription
Security Protocols	Any general security protocols that may result from the implementation of the AI use case.	SecurityProtocols
Data Retention Protocols	Any data retention standards already in place or projected to be implemented for the AI use case.	DataRetentionProtocols
Data Privacy Risks	Any data privacy risks that may result from processing the AI model within the context of this AI use case and either putting it on the market for external customer use or internal use. For example, is there the risk of a data breach or misuse of data?	DataPrivacyRisks
Data Privacy Risk Score	Number calculated from Risk Assessment.	DataPrivacyRiskScore
Intellectual Property Risks	Inherent Intellectual Property Risks resulting from processing AI Models within this use case and placing them on the market or putting into service for own use. Examples include copyright or patent infringement.	IntellectualPropertyRisks
Ethical Risks	Any ethical risks that may result from processing the AI model within the context of this AI use case and either putting it on the market for external customer use or internal use. For example, is there the risk of a data breach or misuse of data?	EthicalRisks
Other Risks	Other Risks resulting from processing AI Models within this use case and placing them on the market or putting into service for own use. Examples can include safety and reliability, security, social risks.	OtherRisks
Business Risks	A summary of the business risks associated with implementing the AI use case. For example, the expected financial loss resulting from significant disruptions to the business due to the complexity of operating the AI model.	BusinessRisks
Overall Risk Analysis	Details and the result of any risk analysis performed on the AI use case.	OverallRiskAnalysis
Overall Risk Rating	Risk level calculated based on pre-defined thresholds in the default Risk Assessment.	OverallRiskRating
Transparency Disclosure Requirements	Transparency Disclosure Requirements refers to identified requirements, if any, for AI use case transparency. For example, a Transparency Declaration that requires an organization to disclose the purpose of the AI model and any data used for training purposes.	TransparencyDisclosureRequirements
Protective Measures	Any additional required or recommended actions that have been identified based on regulations, industry standards or dedicated frameworks.	ProtectiveMeasures
Safeguard Effectiveness	Indicates the effectiveness of the safeguards in place.	SafeguardEffectiveness

Domain type

AI Use Case assets can be created in domains of type Business Asset Domain.

Asset statuses

Phase	Asset status	Description
Core phase	Ideation	You can use this status for suggestions, opportunities, or proofs of concept.
	Development	You can use this status to show that a review has taken place and development work has started.
	Monitoring	You can use this status to show that a release has been made and monitoring is taking place for potential performance, reliability, and accuracy risks.
Retirement phase	Rejected	You can use this status for projects that have been canceled or aren’t being considered for future production. They're in storage for future reference.
Retirement phase	Archived	You can use this status for projects that have been closed and are no longer in production. They are in storage for future reference.

Tip For information on editing the status of an asset, go to Edit an asset.

Create an AI Command Center operating model diagram view

You can create an AI Command Center diagram view, to visualize the operating model. The following procedure describes how to quickly create a new diagram view by copying and pasting the JSON code in the diagram view text editor.

Steps

Open the asset page.
Click the Diagram tab.
The diagram is shown in the default diagram view.
Click to add a new view.
Select the Text option below the diagram view name.
The diagram view text editor is shown.
Copy the code from the Show JSON code section below and paste it in the diagram view text editor.
Click Save.
Edit the name and description of the diagram view as needed.

Show JSON code

Copy

{
  "nodes": [
    {
      "id": "AI Use Case",
      "type": {
        "id": "00000000-0000-0000-0000-000000031401"
      },
      "fields": [],
      "editorSettings": {
        "edgePropsExpanded": true,
        "nodePropsExpanded": false
      }
    },
    {
      "id": "AI Model Version",
      "type": {
        "id": "00000000-0000-0000-0000-000000031402"
      },
      "editorSettings": {
        "nodePropsExpanded": false,
        "filterPropsExpanded": true
      }
    },
    {
      "id": "Vendor",
      "type": {
        "id": "00000000-0000-0000-0000-000000031403"
      },
      "layoutRegion": "flow"
    },
    {
      "id": "Assessment Review",
      "type": {
        "id": "00000000-0000-0000-0000-000000031305"
      }
    },
    {
      "id": "Policy",
      "type": {
        "id": "00000000-0000-0000-0000-000000031202"
      }
    },
    {
      "id": "Training Data (Asset)",
      "type": {
        "id": "00000000-0000-0000-0000-000000031000"
      }
    },
    {
      "id": "Inference Data (asset type group)",
      "type": {
        "id": "00000000-0000-0000-0000-000000031000"
      }
    },
    {
      "id": "Output Data (asset type group)",
      "type": {
        "id": "00000000-0000-0000-0000-000000031000"
      }
    },
    {
      "id": "AI Agent",
      "type": {
        "id": "00000000-0000-0000-0000-000000031450"
      }
    },
    {
      "id": "AI Agent Version",
      "type": {
        "id": "00000000-0000-0000-0000-000000031452"
      }
    },
    {
      "id": "AI Agent Tool",
      "type": {
        "id": "00000000-0000-0000-0000-000000031453"
      }
    },
    {
      "id": "AI Project",
      "type": {
        "id": "00000000-0000-0000-0000-000000031420"
      }
    },
    {
      "id": "AI Base Model",
      "type": {
        "id": "00000000-0000-0000-0000-000000031422"
      }
    },
    {
      "id": "AI Model Deployment",
      "type": {
        "id": "00000000-0000-0000-0000-000000031500"
      }
    },
    {
      "id": "AI Endpoint",
      "type": {
        "id": "00000000-0000-0000-0000-000000031501"
      }
    },
    {
      "id": "AI Monitor",
      "type": {
        "id": "00000000-0000-0000-0000-000000031502"
      }
    },
    {
      "id": "Storage Container",
      "type": {
        "id": "00000000-0000-0000-0001-002900000002"
      }
    },
    {
      "id": "AI Agent Deployment",
      "type": {
        "id": "00000000-0000-0000-0000-000000007505"
      }
    }
  ],
  "edges": [
    {
      "from": "AI Model Version",
      "to": "Vendor",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007105"
      },
      "roleDirection": true
    },
    {
      "from": "AI Use Case",
      "to": "AI Model Version",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007098"
      },
      "roleDirection": true
    },
    {
      "from": "AI Use Case",
      "to": "Assessment Review",
      "label": "",
      "type": {
        "id": "00000000-0000-0000-0000-000000007097"
      },
      "roleDirection": true
    },
    {
      "from": "AI Use Case",
      "to": "Policy",
      "label": "",
      "type": {
        "id": "00000000-0000-0000-0000-000000007018"
      },
      "roleDirection": true
    },
    {
      "from": "AI Use Case",
      "to": "Output Data (asset type group)",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007101"
      },
      "roleDirection": true
    },
    {
      "from": "Policy",
      "to": "AI Model Version",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007018"
      },
      "roleDirection": false
    },
    {
      "from": "Training Data (Asset)",
      "to": "AI Model Version",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007102"
      },
      "roleDirection": false
    },
    {
      "from": "AI Model Version",
      "to": "AI Model Version",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007106"
      },
      "roleDirection": false
    },
    {
      "from": "AI Use Case",
      "to": "AI Agent",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007109"
      },
      "roleDirection": true
    },
    {
      "from": "AI Agent",
      "to": "AI Agent",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007110"
      },
      "roleDirection": true
    },
    {
      "from": "AI Agent",
      "to": "AI Agent Version",
      "label": "",
      "style": "boxing",
      "type": {
        "id": "00000000-0000-0000-0000-000000007206"
      },
      "roleDirection": true
    },
    {
      "from": "AI Agent Version",
      "to": "AI Agent Tool",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007207"
      },
      "roleDirection": true
    },
    {
      "from": "AI Agent Version",
      "to": "AI Endpoint",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007210"
      },
      "roleDirection": true
    },
    {
      "from": "AI Agent Tool",
      "to": "AI Endpoint",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007209"
      },
      "roleDirection": true
    },
    {
      "from": "AI Use Case",
      "to": "AI Project",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007112"
      },
      "roleDirection": true
    },
    {
      "from": "AI Project",
      "to": "AI Model Version",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007111"
      },
      "roleDirection": true
    },
    {
      "from": "Policy",
      "to": "AI Base Model",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007018"
      },
      "roleDirection": false
    },
    {
      "from": "AI Use Case",
      "to": "Training Data (Asset)",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007100"
      },
      "roleDirection": true
    },
    {
      "from": "AI Use Case",
      "to": "Inference Data (asset type group)",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007099"
      },
      "roleDirection": true
    },
    {
      "from": "AI Base Model",
      "to": "AI Base Model",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007116"
      },
      "roleDirection": true
    },
    {
      "from": "AI Model Version",
      "to": "AI Model Deployment",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000077001"
      },
      "roleDirection": true
    },
    {
      "from": "AI Model Deployment",
      "to": "AI Endpoint",
      "label": "",
      "style": "boxed",
      "type": {
        "id": "00000000-0000-0000-0000-000000077006"
      },
      "roleDirection": true
    },
    {
      "from": "Inference Data (asset type group)",
      "to": "AI Model Deployment",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000077003"
      },
      "roleDirection": false
    },
    {
      "from": "AI Model Deployment",
      "to": "Output Data (asset type group)",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000077004"
      },
      "roleDirection": true
    },
    {
      "from": "AI Monitor",
      "to": "AI Model Deployment",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000077007"
      },
      "roleDirection": false
    },
    {
      "from": "AI Model Version",
      "to": "AI Agent",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007108"
      },
      "roleDirection": false
    },
    {
      "from": "Storage Container",
      "to": "AI Agent",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007115"
      },
      "roleDirection": true
    },
    {
      "from": "AI Base Model",
      "to": "AI Model Version",
      "label": "",
      "style": "boxing",
      "type": {
        "id": "00000000-0000-0000-0000-000000077000"
      },
      "roleDirection": true
    },
    {
      "from": "AI Use Case",
      "to": "AI Base Model",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000077002"
      },
      "roleDirection": true
    },
    {
      "from": "AI Base Model",
      "to": "Vendor",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000077005"
      },
      "roleDirection": true
    },
    {
      "from": "Storage Container",
      "to": "AI Model Version",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007114"
      },
      "roleDirection": false
    },
    {
      "from": "AI Agent Version",
      "to": "AI Agent Deployment",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007213"
      },
      "roleDirection": true
    },
    {
      "from": "AI Agent Deployment",
      "to": "AI Endpoint",
      "label": "",
      "style": "boxed",
      "type": {
        "id": "00000000-0000-0000-0000-000000007214"
      },
      "roleDirection": true
    },
    {
      "from": "AI Monitor",
      "to": "AI Agent Deployment",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007215"
      },
      "roleDirection": true
    },
    {
      "from": "AI Agent Tool",
      "to": "Output Data (asset type group)",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007212"
      },
      "roleDirection": true
    },
    {
      "from": "Inference Data (asset type group)",
      "to": "AI Agent Tool",
      "label": "",
      "style": "arrow",
      "type": {
        "id": "00000000-0000-0000-0000-000000007211"
      },
      "roleDirection": false
    }
  ],
  "showOverview": false,
  "enableFilters": false,
  "showLabels": true,
  "showFields": true,
  "showLegend": false,
  "showPreview": false,
  "visitStrategy": "directed",
  "layout": "HierarchyLeftRight",
  "maxNodeLabelLength": 50,
  "maxEdgeLabelLength": 30,
  "layoutOptions": {
    "compactGroups": false,
    "componentArrangementPolicy": "topmost",
    "edgeBends": true,
    "edgeBundling": true,
    "edgeToEdgeDistance": 5,
    "minimumLayerDistance": "auto",
    "nodeToEdgeDistance": 5,
    "orthogonalRouting": true,
    "preciseNodeHeightCalculation": true,
    "recursiveGroupLayering": true,
    "separateLayers": true,
    "webWorkers": true,
    "nodePlacer": {
      "barycenterMode": true,
      "breakLongSegments": true,
      "groupCompactionStrategy": "none",
      "nodeCompaction": false,
      "straightenEdges": true
    }
  }
}