Power BI AI: Ask Questions and Verify the Analysis

Power BI AI can help you ask questions about report data, draft calculations, and explain results. Use it as the start of an analysis: confirm the measure, inspect the filters, reproduce important numbers, and review the conclusion before making a decision.

A useful answer needs a trail back to the report that produced it. fenbs can keep report links, agreed metric definitions, assumptions, and reviewed conclusions together so your next assistant starts from the same evidence. Power BI remains where you model and analyze the data.

How do you start an analysis you can check?

1. Choose one report and one question. For example, ask which US sales regions contributed most to a decline in completed orders between two closed months.
2. Write down the expected measure, time period, comparison, and exclusions. Define whether an order counts when placed, shipped, or completed.
3. Confirm that the report has refreshed and that you can access the required data. Note the refresh time and the filters visible on the page.
4. Ask AI for a result table and a short explanation. Request the calculation behind the answer when that experience makes it available.
5. Check the largest contributors against an ordinary report table before accepting the summary. Save the reviewed answer with its scope and remaining questions.

Do this first with a question whose answer you already know. You will learn whether the assistant interprets your business terms correctly without relying on an untested result. A successful demonstration should match the number and its meaning, including what was left out.

What must be clear before you ask a question?

Power BI uses a semantic model, the organized tables, relationships, and measures behind a report. Business terms should point to the right part of that model. “Revenue” might mean billed revenue in one report and collected payments in another; neither a polished chart nor a confident explanation settles that choice.

Microsoft says that preparing the model and its users matters to the quality of Copilot output in its semantic model guidance↗ (opens in a new tab). Confirm the intended model with its owner before exploring a sensitive or unfamiliar measure.

• Meaning: the business definition and approved measure name.
• Coverage: the source system, included locations, and latest complete reporting period.
• Context: date filters, currency, canceled transactions, and any restricted view of the data.
• Expected use: an exploratory question, a management update, or evidence for a consequential decision.

Keep those definitions close to the report link. A note saying “exclude canceled orders” is only useful if the next analyst knows which analysis it applies to. The AI approval workflow guide explains how to keep an investigation separate from permission to act.

How should you phrase the analysis request?

Ask for a bounded comparison before asking why it happened. Say which approved measure to use, how to group the result, and what comparison period applies. Ask the assistant to state any interpretation it had to make instead of silently filling gaps.

Do not ask a long chain of questions that changes the population halfway through. First establish the totals, then investigate the breakdown, then consider explanations. Keep each follow-up attached to the same period and measure unless you explicitly change the scope.

When an answer surprises you, ask what data would distinguish competing explanations. A regional decline could reflect fewer customers, a reporting delay, or a changed territory assignment. Finding the largest difference does not establish its cause.

How do you verify generated calculations?

DAX is the formula and query language used in Power BI models. When an AI experience exposes a DAX query, read the fields, measures, date logic, grouping, and filters before running or reusing it. Valid syntax means the code can be understood by the system; it does not mean it answers your question.

Microsoft’s data question documentation↗ (opens in a new tab) describes inspecting available query and table results. The controls depend on the experience you are using. If you cannot inspect enough evidence to verify an answer, ask the model owner to reproduce it through a known report or reviewed query.

Compare the output with a simple table using the approved measure and identical filters. Check one small slice by hand or against a source-system total. Include a zero-result period, a blank category, and a selection involving multiple regions if those cases matter to the report.

Check totals independently. Percentages and averages often cannot be added across rows, and a total can have a different calculation context from a visible detail row. If the assistant drafts a reusable measure, test it in the report contexts where people will actually use it.

What makes a summary ready to share?

A shareable summary names the measure, population, period, and observed change. Its explanations should match the returned numbers. Replace “customers prefer another product” with “completed orders declined in this segment; the report does not identify why” unless you have separate evidence for the preference claim.

Record what someone reviewed. “Checked against the report table with the same filters” is more informative than “AI verified it.” Add the report link, refresh time, reviewed calculation, and any unresolved discrepancy. Use fenbs’s shared work record to keep that evidence beside the person’s accepted conclusion.

How to do this with fenbs

1. Create a free account, then add a project for the analysis you need to finish.
2. Add the report and source references in Links and listings, and put agreed metric definitions in the project glossary or context notes.
3. Create a task for the question. Include the period, filters, comparison, review plan, and links to the evidence available to the reviewer.
4. Record the person’s accepted conclusion and any continuing review rules in Decisions and rules. Save progress with what was checked and what the next session must resolve.

fenbs does not run Power BI queries or connect to Power BI reports. Use it for the work record when analysis crosses sessions or assistants; a single report comment may be enough for a small one-time question. The Power BI assistant connection guide covers a separate connection question.

Where should you go for a different analysis problem?

For adjacent tasks, use the guides to Power BI AI Insights, sentiment analysis, text analysis, competitor analysis, or Power Automate workflows. Each needs its own inputs and checks. The AI at work hub brings those workflows together.