AI Agent: Adaptive Cards for Newsletters

Key insights

• Generative Adaptive Cards: AI automatically creates and adapts card-based UI elements for Microsoft 365 apps, letting teams build interactive, data-driven interfaces faster.
  These cards render in chat and app hosts like Teams and Outlook for consistent user experiences.
• Adaptive Cards: Cards use JSON to define layout, buttons, inputs, and charts so hosts can render the same UI across platforms.
  Using AI removes much of the manual JSON crafting and speeds deployment.
• Copilot Studio: Copilot Studio accepts natural-language prompts to generate ready-to-use Adaptive Card JSON and to build custom agents that produce cards during conversations.
  Example use: generate buttons for each Power Platform product that show short descriptions on click (Power Apps, Power Automate, Power Pages, Power BI, Copilot Studio).
• JSON: The card structure is JSON-based, and AI generates valid JSON so you can copy, paste, and embed cards without hand-coding.
  AI also adds data bindings and conditional elements for dynamic content.
• Power Platform: Generative cards integrate with Power Automate, Power BI and other Power Platform tools to trigger workflows, show charts, and connect to live data.
  This makes cards practical for automation, reporting, and guided user flows.
• Context-aware generation: The system tailors cards to conversation context, supports error handling and retries, and enables low-code/no-code workflows for non-developers.
  Expect richer controls, charts, and agent-driven personalization as best practices and training resources roll out.

Overview of the video

In a concise YouTube update, Audrie Gordon demonstrates how to generate Adaptive Cards inside Microsoft 365 Copilot and Copilot Studio. The video, framed as a weekly tip, shows a practical, no-code workflow that aims to speed card creation for chat and collaboration scenarios. Viewers see a real prompt and the resulting cards, which makes the concept tangible for both makers and IT professionals. Consequently, the clip serves as a practical primer rather than a deep technical tutorial.

The prompt and demonstration

Gordon opens the demo by sharing the exact natural-language prompt she used to ask Copilot to design a card that lists five Power Platform products and provides short descriptions when buttons are pressed. She explains how she asked for the card in a copyable JSON format, which lets users paste the output directly into Copilot Studio for quick testing. As a result, viewers can follow the same pattern to create cards tailored to their own apps without hand-writing complex JSON. This step-by-step display emphasizes ease of use while showing the prompt engineering that produces reliable JSON output.

How Generative Adaptive Cards work

Adaptive Cards are JSON templates that render interactive UI across Microsoft apps, and the video highlights how generative AI automates that JSON creation. In practice, Copilot interprets conversational context and the author’s intent, then produces a card layout with elements like buttons, text blocks, and conditional actions. Moreover, Gordon points out that the AI can adapt content dynamically based on the prompt, resulting in cards that reflect user preferences or business context. Thus, the approach reduces manual design work and lowers the barrier for non-developers.

In addition, the demonstration shows how generated cards can integrate with Power Platform tools, enabling conditional logic and branching through connectors and flows. By combining the generated JSON with automation tools such as Power Automate, makers can wire up actions that update systems, collect inputs, or navigate multi-step dialogs. However, the video also notes that production deployment often needs further validation to ensure data bindings and triggers work correctly. Therefore, the generative step accelerates development but does not eliminate testing and integration effort.

Benefits for teams and makers

The video makes a clear case that generative cards speed up prototyping and internal communication, helping teams iterate faster and deliver richer chat experiences. Consequently, designers and citizen developers can move from idea to working sample in minutes, which increases alignment and reduces friction in early-stage projects. Additionally, the cards support enhanced UX elements like buttons, badges, and charting, which improves clarity and engagement for end users. As a result, organizations gain both speed and polish while making conversational interfaces more useful.

Tradeoffs and challenges

Despite the advantages, Gordon’s demonstration also hints at important tradeoffs, particularly around quality control and governance. Generative outputs can vary in structure and accuracy, so teams must validate JSON, test error handling, and confirm accessibility and localization requirements. Furthermore, relying on AI for layout and behavior decisions may require stronger review processes and version control to prevent unwanted changes in production. In short, the convenience of generation comes with the need for disciplined validation and oversight.

Another challenge involves balancing no-code speed with the need for custom control, especially for complex workflows that depend on precise triggers or conditional logic. While the AI can scaffold many use cases, advanced scenarios often still require manual edits or developer intervention to optimize performance and security. Finally, enterprises must weigh governance policies, data residency, and compliance needs when exposing AI-assisted design tools to broader teams. Therefore, organizations should pair generative capabilities with clear policies and testing practices.

Practical recommendations and next steps

For teams interested in adopting this approach, the video suggests starting with simple prototypes and adding validation layers as complexity grows, which helps balance speed and reliability. In practice, pilot projects can use generated cards for internal workflows while the security and integration teams establish templates and review gates for production. Additionally, training and documentation will help citizen developers use prompts effectively and follow best practices when modifying generated JSON. Finally, Audrie mentions a forthcoming course that will teach no-code Adaptive Card building, which could accelerate adoption while emphasizing practical safeguards.

Keywords

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