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Integrating AI using Developer Tools for Copilot

Artificial Intelligence is no longer just a buzzword; it is a fundamental building block of modern business applications. Microsoft is accelerating this shift by equipping developers with a robust set of tools to weave generative AI and Copilot experiences directly into Dynamics 365 Business Central.

For developers and organizations looking to move beyond out-of-the-box features, the Developer Tools for Copilot open up a new world of possibilities. You can now build custom AL (Application Language) extensions that harness the power of AI to automate tasks, generate insights, and interact with users through natural language.

Here is a breakdown of what the developer toolkit includes and how you can start building custom Copilot capabilities today.

1. Extending Copilot with AL

Microsoft provides a dedicated AI module (System.AI) within the base application, serving as the bridge between your Business Central environment and powerful generative AI models. Developers can use this module to connect seamlessly to the Azure OpenAI Service, allowing you to bring advanced capabilities—like text summarization, data analysis, and predictive suggestions—directly into your custom workflows.

2. Crafting the User Experience

To ensure that custom AI features feel native to Business Central, Microsoft introduced the PromptDialog page type. This allows developers to create standard, intuitive conversational interfaces.

  • Prompt Guides and Floating Action Bars: You can build user experiences that guide employees on how to prompt the AI effectively, ensuring they get the best results without needing to be “prompt engineers.”

  • Built-in Error Handling: The tools come with native error handling for prompt dialogs, ensuring that if an AI model encounters an issue or hits a token limit, the user is guided gracefully to a solution.

3. Advanced Capabilities: Function Calling and Token Counting

Developing reliable AI tools requires precision. The developer toolkit includes advanced features to optimize how your extensions interact with Language Models (LLMs):

  • Function Calling: You can configure the AI to trigger specific AL functions based on user intent. For example, if a user types, “Update the inventory levels for Item A,” the Copilot can map that natural language request directly to your custom inventory-update codeunit.

  • Token Counting: To manage API costs and optimize performance, the tools provide token counting mechanisms, giving developers control over the size and scope of the data being sent to and received from the LLMs.

4. Zero-Code Influence on Agents

Not every AI enhancement requires deep coding. The latest updates also outline concepts for influencing Copilot and autonomous agents without extending them. By optimizing your data structures, standardizing workflows, and refining how your fields are labeled, you can improve how the native Copilot interprets your specific business environment out-of-the-box.

5. Responsible AI at the Core

With great power comes the need for governance. Microsoft emphasizes ethical development by integrating frameworks for Responsible AI. Developers have access to the Azure AI Foundry portal for safe experimentation, ensuring that the custom Copilot features you build adhere to transparency, privacy, and security standards.

Getting Started

Ready to build your first AI-powered AL extension? The best place to start is by setting up your Azure OpenAI Service connection and exploring the sample extensions available in the BCTech GitHub repository.

By leveraging these developer tools, you can transform Business Central from a reactive system of record into a proactive, intelligent partner tailored precisely to your unique operational needs.

Dive into the complete documentation, tutorials, and code samples on the Microsoft Learn Copilot Integration Hub.

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