Demonstrating Client Feature Value with Dataverse, AI Builder
In this video, UG Expert Kylie Kiser demonstrates how to generate client-facing impact statements for new features by using Dataverse and AI Builder in the Power Platform.
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Key Takeaways
- Overview: In this video, Kylie is using GPT to generate initial client impact statements for new features by leveraging information stored in Dataverse and an AI builder prompt. In her upcoming videos, Kylie will demonstrate the process that involves setting up a table in Dataverse to store data, creating an AI prompt, and developing a flow to generate client impact statements using the AI builder prompt.
- Create a table: In the solution, Kylie creates a new table called “feature.”Initially, no additional items will be added, but columns will be added later through the form.
- Add details: In the new main form, the feature name is kept, and additional fields such as feature description and feature value areas will be added as multiple lines of text. Last, a client impact field, which will be AI-generated, will also be included.
- From form to app: All the fields, including the client impact, are being added to the form and resized for better visibility. After saving, the form will be placed in an app.
- What’s next: In this case, an existing app will be used to add the new feature for visibility. Part 1 of this video series covers model-driven app customization, while the next videos will focus on AI builder prompts and flows.
