The business question What are our AI dependencies? visualizes a network diagram that helps you understand the relationships between the different parts of the AI portfolio. Review the AI use cases that are supported, the AI features included in those use cases, the AI models and AI technologies used, and the business capabilities that are affected by the AI architecture. You can perform an impact analysis on the AI portfolio from any perspective and, for example, assess the consequences to the AI portfolio if an AI feature or AI model is discontinued. This business questions helps you to understand your AI architecture in order to manage its complexity, avoid potential risks, and ensure compliance with AI regulations.
The license package Enterprise Portfolio Management is required to work with this business question. The use case AI Portfolio Management must be activated.
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What information is displayed in What are our AI dependencies?
A filter setting is mandatory for this business question. Click the 
local filter button and specify any of the Global Filter fields.
The network diagram visualizes the relationships between the different parts of the AI portfolio so that you can execute an impact analysis on aspects of the AI.
- The network diagram shows the connections between AI use cases
, AI features 
, AI models 
, AI technologies 
, and business capabilities. - Click the local filter button and select the relevant AI asset to focus on and understand its relationship to other AI assets in the architecture.
- The AI features show symbols for the applications
and components 
and AI technologies that provide the feature. Point to the symbol to show the name in a tooltip. Double-click the symbol to navigate to the content area of the AI architecture element.
Click the 
3-dots button > Change Layout to open the diagram designer and change the layout and styling of flow reports and network diagrams.
What data is required for What are our AI dependencies?
Business question: What are our AI dependencies?
Purpose: Understand the AI architecture including the AI use cases that are supported, the AI features included in those use cases, and the AI models and AI technologies used.
DATA REQUIREMENTS
Capture the data necessary for the business question. The AI architecture must be in the repository and well documented.Capture AI Use Cases ,AI features , AI models , and AI technologies as possible because complete data considerably improves the results of the business question and your ability to focus on the data that is most important to you.
- Assign AI features to the AI use case
- Assess the risk level of the AI use case
- Review the approval details of the AI use case
- Specify the AI feature's attributes Specify the AI feature#s attributes including the enabling AI models, enabling AI technologies, providing application, providing component, and risk level and approval status.
- Specify the AI technology's attributes including its approval status.
- Add the AI technologies that the AI model provides.
Improve the data and correct data quality issues. Go to the business question's Data Quality > Data Completeness. This visualization helps you to assess whether sufficient data is available to produce meaningful and reliable results for the business question.
- Go to Pending Issues to resolve data quality issues and improve the data that the business question is based on. Only the first 5000 issues are displayed.
- Go to the Data Source page to understand the underlying data relevant to the business question. The data source is a list report and cannot be edited.