Last updated: Oct 25, 2024
Create an AI use case to track and govern AI assets from request through production. Factsheets capture details about the asset for each stage of the AI lifecycle to help you meet governance and compliance goals.
Governance details for tracked assets are collected in an AI use case and stored in an inventory. A typical flow to request and track an asset is as follows:
- A business user (the model owner) identifies a need for an AI solution and creates an AI use case to request a new model.
- When the request is saved, the AI use case is created in the inventory, and the tracking begins. Initially, the use case is in the Draft state because there are no assets to accompany the request. Optionally, you can implement a manual approval process as simple as sending a link to an approver and getting a sign-off in email before sending the use case to a data scientist or prompt engineer. Or, you can implement a more structured sign-off process by adding an attachment group to the use case that adds a placeholder for uploading a formal approval document as part of your governance plan.
- When the AI use case is fully set and approved, the owner moves it to the Awaiting development status and sends the link to the assigned data scientist or prompt engineer.
- When the assigned developer creates a model for the use case, they associate the asset with an _approach in the use case. An approach is one path for solving the problem in the use case. A use case can include multiple approaches.
- Once tracking is enabled, details for tracked assets are captured in factsheets and stored in the use case. For example, the factsheet for a machine learning model includes training data and creation details.
- As the asset advances in the lifecycle, the AI use case and the factsheets capture all updates, including deployments and evaluation results.
- The use case owner continues to update the status to reflect the current state in the lifecycle.
- Validators and other stakeholders can review AI use cases to ensure compliance with corporate protocols and to view and certify model progress from development to production. The user can generate reports from the use case to archive details or satisfy compliance requirements.
Get started with AI use cases
Set up or work with AI use cases:
- Create an inventory for storing AI use cases
- Set up an AI use case
- Track assets in an AI use case
- View factsheets for tracked assets
Parent topic: Governing AI assets