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Prepare your data for AI: AI instructions

Preparing your data for AI in Power BI involves optimizing your semantic model to enhance the performance of Copilot. When you use features like AI instructions, you can provide context and guidance that improve the relevance and accuracy of AI-driven insights. This guide walks you through the steps to set up and test AI instructions, to help prepare your data for AI-powered analysis.

AI instructions allow model authors to provide context, business logic, and specific guidance directly on the semantic model. Copilot uses these instructions to better interpret user questions by incorporating organizational language, terminology, and analytical priorities that Copilot wouldn't otherwise understand on its own.

These instructions help clarify business terms, guide analysis approaches, and provide critical data context. After you save the instructions, Copilot uses them to respond more intelligently to user prompts.

AI instructions make Copilot more aligned to your business. They improve the quality and relevance of responses by reducing ambiguity and ensuring that Copilot understands your domain-specific terms and analysis expectations. Ultimately, this practice leads to more meaningful insights, less user frustration, and a smoother experience with Copilot across reports that use the same model.

Set up AI instructions

Note

You can now author Prep data for AI features in both the Power BI service and Power BI Desktop. Users can consume these features everywhere that Copilot exists.

  1. Select the Prep data for AI button located on the Home ribbon in Power BI Desktop, or on the ribbon on the selected semantic model in the Power BI service.

    Screenshot that shows the Prep Data for AI feature in Power BI Desktop.

    If the tabs in Prep data for AI are disabled, enable Power BI Q&A for your model.

    Screenshot that shows how to enable Q&A for the model in Power BI Desktop.

  2. In the dialog, go to the Add AI instructions tab.

  3. Provide instructions about the semantic model that help Copilot understand your business, terminology, and how to prioritize the data in the model.

    Screenshot that shows a dialog that features the AI instructions tab in Power BI Desktop.

  4. Select Apply.

After you close the dialog, your changes are saved to your model. Copilot now uses the AI instructions.

Test AI instructions in Power BI Desktop

  1. Open the Copilot pane in Power BI Desktop.
  2. Use the skill picker to select the specific Copilot capability you want to test. We recommend that you choose Answers questions about the data.
  3. Interact with Copilot by utilizing one of the instructions that you set.
  4. Ensure that Copilot responds accurately.
  5. If you need to change the instructions, reopen the Prep data for AI dialog and adjust.
  6. Publish or save your report. When you finish testing and are satisfied with the AI instructions, publish your report to the Power BI service.

Note

Each time you edit an instruction in the Prep data for AI dialog, you need to refresh the Copilot pane by closing and reopening it.

Consume AI instructions

After your report is published to the Power BI service, or changes are saved in the service, users can take advantage of the AI instructions everywhere that model interacts with Copilot.

Note

End users can't see the AI instructions set on the model.

Common use cases for AI instructions

AI instructions offer a flexible way to enhance how Copilot interprets and responds to user prompts. Although there are many potential applications, two common use cases stand out: general business context and data interpretation and analysis rules.

General business context and data interpretation

Instructions can help Copilot frame responses within the context of your business, tailoring answers based on your industry, strategic goals, terminology, or operational logic. When you use instructions, you can help ensure that users get more accurate and relevant insights. Some examples include:

  • Busy season is October to February.
  • Frame insights with a focus on risk assessment and market trends.
  • When a user mentions ABCD, they're referring to the total invoice field.
  • A lower attrition percent is more positive.

Analysis rules

You can guide Copilot on how to approach certain types of analysis by providing rules and preferences for how data should be sliced or prioritized. Some examples include:

  • Always analyze sales on a quarterly basis.
  • When showcasing revenue, break it down by quarter and compare it to the industry field.
  • For retail insights, prioritize the customsegmentationtable and saleschannel tables.
  • Use the sales_fact table as the primary source for all sales-related questions.
  • When a user asks about product sales, always ask for clarification on location.

Prompt engineering for AI instructions

Because AI instructions are heavily prompt-based, it's important to understand best practices for prompt engineering as you build out your instructions for a semantic model. Copilot can be sensitive to the prompts that it receives, so prompt construction affects Copilot outputs. Here are some ways to get the most out of your AI instructions, including an example of best practices in action.

Be explicit and specific

Assume Copilot has no understanding of how to use the data model or business context for your data. For example, instead of writing "You're a seasoned BI Analyst who is detail oriented," consider: "You're a seasoned BI Analyst who works for a big food distributor. Responses should be detail oriented and focused on revenue and profitability."

Use analogies and descriptive language

When you use analogies and descriptive language, you help the model understand your desired outcome. Examples can also play a vital role in helping the model understand exactly what you mean. For example, for product-specific sales, use the measure Total_Sales_Product (example of product: Word, PowerPoint, Excel, SharePoint, Teams).

Avoid ambiguity

Be clear about anything that you want Copilot to emphasize or avoid. The more details and supporting content you can provide Copilot, the better. For example, for Total Active Partners, use the measure Monthly Active Partner Count. (Don't filter on the Customers table.)

To help Copilot better understand your intent, organize instructions by theme or purpose (like date logic, key metrics, and industry terms). It can be beneficial to include structural elements, such as sections, hierarchies, and headers. For an example of how to group related instructions in the full set of instructions, see the example scenario.

The order in which you author instructions can affect the output you receive

You can boost your chances of getting correct outputs by testing different variations, orders, examples, and wording.

Break down complex instructions into simpler steps

When you break down instructions into simple steps, you can improve clarity and reduce errors. For example, define top customers by first looking at the revenue table and then returning only the customers with the highest order values.

Keep instructions focused

Depending on the model and the instructions you set, sometimes less is more. Conflicts and complexity in instructions can cause confusion for large language models (LLMs).

Example scenario

The following example scenario shows a set of AI instructions that are prompt engineered to fit a specific model.

Instructions for answering data questions

Gross product sales (GPS) should reference the grossrevenue field in the Revenue table.

Top sellers refers to the top three partners with the highest revenue. Don't show customers unless the user explicitly asks.

Customer identification

  • accountid refers to customers in the Revenue table.
  • earningsid refers to customers in the Partners table.
  • customid in the order table doesn't refer to customers.
  • Define top customers by first looking at the revenue table and then returning only the customers with the highest order values.
  • Some partners are also customers. Don't remove these duplicates. Instead, indicate whether it's a partner or a customer based on the ID value.

Product metrics

  • Filter data by State= Washington or State= California unless the user specifically asks for a different state.

  • For product specific sales, use the measure Total_Sales_Product (example of product: Word, PowerPoint, Excel, SharePoint, or Teams). Filter on the Product column from the Sales table.

  • For Total Active Partners, use the measure Monthly Active Partner Count_ID. (Don't filter on the Customers table.)

  • Food product sales are always from retail stores.

    If the value product_type in the Product table is Food, then always show the store where the item was sold. Store information is found in the Store table with the field store_name, and it can be linked to product_type by store_id.

Note

You often need to iterate to get the most benefit from AI instructions. As you experiment and observe how Copilot responds, you develop a better understanding of what types of instructions drive the best outcomes for your model and your users.

Considerations and limitations

  • Because AI instructions are unstructured guidance to Copilot, the LLM only interprets them. There's no guarantee that the LLM will exactly follow instructions.
  • AI instructions affect Copilot capabilities but don't extend to general conversations with Copilot.
  • AI instructions are saved at the semantic model level. Instructions can't currently be stored at the report level.
  • AI instructions aren't expected to be persona-specific or modify non-data-related outputs for the end user.
  • AI instructions can't disable other Copilot in Power BI features or prevent/prioritize certain features from being called.
  • Instructions aren't intended to work with visual modifications or theming in your report.
  • Currently, you can't upload instructions to the dialog in Desktop.
  • To test instructions in Desktop, you need to close and reopen your Copilot pane to see new instructions applied.
  • Users can't set instructions by category or by mode (view or edit) in Copilot in Power BI.
  • Consumers can't see what instructions an author applied to the model in the UI.
  • End users can't disable instructions on a semantic model.
  • AI instructions might not be respected in Power BI Desktop when you're trying to create a page, get suggested report page topics, or a dataset summary with Copilot. To work around this issue, use the skill picker and select only Create new report pages to have instructions successfully apply.
  • AI instructions are limited to 10,000 characters.

For a comprehensive list of considerations and limitations, see Prepare your data for AI.

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