What is Copilot in Power BI and how does it work?

Copilot is an integrated AI assistant in Power BI that allows users to ask questions of the report in natural language and receive visual and textual answers instantly. A manager can type a question about sales trends and Copilot queries the underlying data model and returns a chart with a text explanation, without requiring any technical knowledge.

Do you need programming knowledge to use AI features in Power BI?

No. Copilot, Smart Narratives, Anomaly Detection, Forecasting, and Key Influencers are available as built-in features in Power BI without requiring programming or data science knowledge. Any business analyst with basic Power BI knowledge can use them directly from the platform's visual interface.

Artificial Intelligence

Artificial Intelligence in Business Intelligence: Real Use Cases

By Manuel Cosini · March 20, 2026 · 5 min read

Artificial intelligence is no longer a laboratory topic or a future promise. It is a present reality within the Business Intelligence tools used today by companies of all sizes. Power BI, the world's most widely adopted BI platform in the business world, has incorporated AI capabilities natively, and those capabilities are transforming the way teams analyze data and make decisions.

In this article, we review the AI features available in Power BI, how they are used in practice, and what concrete results they generate across different types of businesses.

What Does "AI in Business Intelligence" Mean?

When we talk about artificial intelligence in the context of BI, we refer to a set of capabilities that go beyond static data visualization. AI in BI enables:

Generating analysis in natural language from written questions
Automatically detecting anomalies and statistically significant changes
Producing explanatory narratives about data without human intervention
Projecting future trends using machine learning models
Identifying the key factors that explain variations in critical metrics

All of this is available in Power BI without requiring the user to have programming or data science knowledge.

Copilot in Power BI: Analysis in Natural Language

The incorporation of Copilot in Power BI represents the most profound change in the platform's user experience. Copilot is an integrated AI assistant that allows users to ask questions of the report in natural language and receive visual and textual answers instantly.

How Does It Work in Practice?

Imagine you are the sales manager of a retail company and you open the sales dashboard. Instead of navigating through all the charts to find the insight you are looking for, you simply type in the Copilot panel: "What are the three products with the biggest sales decline last month compared to the previous month?" Copilot processes the question, queries the underlying data model, and returns an answer with the corresponding chart and a text explanation.

This has an enormous impact on democratizing data analysis. Previously, getting that answer required an analyst to build a specific query or a new chart. With Copilot, any business user can explore the data as easily as performing a Google search.

Real Use Cases for Copilot in Power BI

Retail: Store managers asking the report which product categories had the biggest margin variation in the past week.
Logistics: Supervisors asking which delivery routes accumulated the most delays during the month and what the main cause is.
Finance: CFOs asking what the cash flow projection is for the next quarter under different collection scenarios.

Q&A: Natural Language Questions About Your Data

Before Copilot, Power BI already included the Q&A (Questions and Answers) feature, which allows users to type questions in natural language directly into the dashboard and receive an automatically generated visualization as a response.

The difference from Copilot is that Q&A is better suited for simple exploratory queries ("How many sales did I have in March?", "Which category has the most returns?"), while Copilot handles more complex and contextual queries. Both tools complement each other and reduce dependence on the technical team for answering day-to-day business questions.

Smart Narratives: Automatic Explanations of Your Data

One of the historical limitations of dashboards is that they show what happened, but do not explain why. Smart Narratives in Power BI solves this problem by automatically generating explanatory text that accompanies the visualizations.

For example, if the monthly sales chart shows a 15% drop in February, Smart Narratives can automatically generate a paragraph saying: "February sales were 15% lower than January. The majority of the decline was concentrated in the North region (-22%) and the Electronics category (-18%). All other regions and categories showed variations within the normal historical range."

This feature has special value for preparing executive reports: instead of an analyst having to manually write comments for every chart, Power BI generates the text automatically, and the analyst only needs to review and adjust if necessary.

Anomaly Detection: Automatic Alerts on the Unusual

Anomaly detection is one of the most valuable AI applications in the business context. Anomaly Detection in Power BI analyzes the time series of your KPIs and, when it detects a statistically unusual value, marks it automatically on the chart and generates an explanation of which factors contributed to that anomaly.

Real-world examples:

E-commerce: Automatic detection of an unusual spike in product returns on a specific day, which turned out to be associated with an error in size descriptions in the catalog.
Manufacturing: Automatic identification of a drop in the efficiency index of a production line, detected 48 hours before the supervisor noticed it manually.
Financial services: Alert about atypical behavior in a customer's transactions, which enabled a preventive review before a potential fraud.

Automatic anomaly detection does not replace human judgment, but it dramatically expands the company's supervisory capacity: it is impossible for a person to review every metric every day, but AI can.

Forecasting: Automatic Projections with Machine Learning

Power BI includes forecasting capabilities that apply machine learning models to your data's time series to project future values. The user only needs to select the series they want to project, define the time horizon and confidence level, and Power BI automatically generates the projection with confidence bands.

This feature has direct applications in:

Sales planning: Sales projection for the next quarter based on historical data and seasonality.
Inventory management: Estimation of future demand to optimize stock levels.
Financial planning: Projection of revenue and expenses for annual budget preparation.

Key Influencers: Understanding What Moves Your Metrics

The Key Influencers visual in Power BI applies machine learning algorithms to identify which factors have the greatest statistical influence on a target metric. For example, if you want to understand which variables explain customer subscription cancellations, Key Influencers analyzes all available dimensions (region, plan, time as customer, product usage) and tells you which are most correlated with cancellation.

This type of analysis, which previously required a data scientist, is now accessible to any business analyst with basic Power BI knowledge.

Considerations When Implementing AI in BI

AI in Power BI is powerful, but it requires certain conditions to work well:

Data quality: AI models are only as good as the data that feeds them. Inconsistent or incomplete data generates incorrect projections and narratives.
Sufficient data volume: Forecasting and anomaly detection need sufficient historical data to be statistically reliable. In general, at least 12 months of historical data is recommended.
Human review of results: AI can make mistakes or misinterpret the business context. Results should always be reviewed by someone with business knowledge before using them to make important decisions.

Conclusion

Artificial intelligence integrated into Power BI is democratizing capabilities that five years ago required specialized data science teams. Copilot, Smart Narratives, Anomaly Detection, Forecasting, and Key Influencers are concrete tools, available today, that expand what a business team can do with its data without requiring advanced technical knowledge. The challenge is no longer accessing the technology, but knowing where to apply it to generate the greatest impact.

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Frequently Asked Questions

What is Copilot in Power BI and how does it work?: Copilot is an integrated AI assistant in Power BI that allows users to ask questions of the report in natural language and receive visual and textual answers instantly. A manager can type a question about sales trends and Copilot queries the underlying data model and returns a chart with a text explanation, without requiring any technical knowledge.
How does anomaly detection work in Power BI?: Anomaly Detection in Power BI analyzes the time series of your KPIs and, when it detects a statistically unusual value, marks it automatically on the chart and generates an explanation of which factors contributed to that anomaly. This allows companies to identify problems much earlier than a person would by manually reviewing reports.
Do you need programming knowledge to use AI features in Power BI?: No. Copilot, Smart Narratives, Anomaly Detection, Forecasting, and Key Influencers are available as built-in features in Power BI without requiring programming or data science knowledge. Any business analyst with basic Power BI knowledge can use them directly from the platform's visual interface.