Imagine that instead of spending half a day building a sales report, you simply tell the system: “Show me the revenue trend by region for the last quarter” – and within seconds you have a finished chart, complete with insights. This isn’t a scenario from the future. This is AI in Power BI in 2026.
Microsoft Power BI is no longer just a charting tool – it’s a powerful, AI-driven analytics platform that can uncover hidden trends on its own, generate reports from a plain-language description, and translate complex data into something any manager can understand. Copilot in Power BI – an assistant built on the same technology behind ChatGPT – is changing the way companies work with data.
In this article, we’ll show you how Power BI’s built-in AI features work, what Copilot is and how to turn it on, and how to bring modern analytics into your organization – even if your team has never written a single line of code. We’ll walk through the specific data analysis and report automation tools that are changing the daily work of analysts and decision-makers.
Take a look at Data Courage as well – our toolset for simple, prompt-based data analysis.
What Is AI in Power BI, and How Is It Changing Data Analysis?
AI in Power BI isn’t a single button – it’s an entire ecosystem of tools that work both behind the scenes (automatically optimizing data models) and directly in the user’s hands. Some of these features have been around for years; others, like Copilot, are new and are changing the rules of the game.
The Evolution of Power BI: From Static Reports to Intelligent Suggestions
When Power BI launched in 2015, it was primarily a data visualization tool – easier to use than Excel, but still requiring reports to be built by hand. Over time, Microsoft layered in more intelligence: first simple Quick Insights, then machine-learning-based visuals (Key Influencers, Decomposition Tree), and since 2023, Copilot, built on large language models (LLMs).
AI in Power BI doesn’t require Python or R programming skills – although the platform supports both. Most of Power BI’s AI-based features work on a point-and-click basis: you pick a visual, point it at your data, and the algorithm does the rest. That means advanced analytics isn’t limited to the IT department – sales, finance, and logistics teams can use it too.
Why Use AI Features at All?
Power BI’s AI capabilities translate into three concrete business benefits. First, speed. Instead of hours spent manually combing through large datasets, the system identifies patterns, anomalies, and key drivers in seconds. The Insights feature can automatically scan an entire dataset and flag what’s worth a closer look.
Second, it eliminates human error. When you’re working through thousands of rows of data, the human eye misses subtle correlations and trends. Power BI’s algorithms don’t have that limitation – they check every combination of variables and catch what a person would overlook.
Third – and this is the real breakthrough – AI shifts the focus from describing the past to forward-looking data analysis. Forecasting and anomaly detection let you spot trends before they materialize. A company that knows sales in a given region are about to start declining in two months can act proactively, instead of reacting once the losses are already real.
Power BI’s Key Built-In AI Features – Tools Anyone Can Use
Power BI comes with several ready-made AI visuals that require no technical setup at all – you just drag them onto the report canvas and connect them to your data. Below, we cover the four most important ones.
Q&A – Have a Conversation with Your Data
Q&A is natural language processing (NLP) built directly into Power BI. You type a question in plain language – “what was total sales in March by product category?”, for example – and the system automatically generates the right chart. You don’t need to know which table the data lives in or what the column is called.
It’s worth knowing that Microsoft plans to retire the classic Q&A feature in December 2026, replacing it entirely with Copilot. That makes now a good time to start preparing your data models for AI – with descriptive column names, well-defined relationships, and synonyms in your semantic model. You can read more about how AI and BI support business decisions on our site.
Key Influencers – Understand What’s Driving Your Results
Key Influencers is a visual that answers one question: what’s causing a given metric to rise or fall? You point it at the measure you care about – customer churn rate, for example – and the algorithm analyzes every available variable and ranks them by how strongly they influence it.
In practice, that means instead of manually testing dozens of hypotheses, you get a ready-made answer: customers who don’t hear from you within 7 days of purchase churn 3.5 times more often. An insight like that would take an analyst days to find manually – the system generates it in seconds. It’s especially useful for manufacturing and distribution companies, where the number of variables affecting results is very large.
Decomposition Tree — Find the Root Cause
The Decomposition Tree lets you visually break data down into its component parts – clicking through successive branches takes you deeper and deeper into the data structure, right down to the source of an anomaly. Say you see that revenue dropped 12%. You click, and you see the drop was concentrated in the southern region. You click again – and it turns out one customer put their orders on hold.
Importantly, the Decomposition Tree offers an AI Explain mode, where the algorithm suggests on its own which branch is worth expanding – pointing you to the dimension with the biggest impact on the value you’re analyzing. That saves time and reduces the risk of missing an important factor.
Smart Narrative – Automatic Report Summaries
Smart Narrative is a visual that generates a written summary of a report’s key takeaways – automatically, in real time. Instead of making a director pick through five charts, the system writes a ready-made paragraph along the lines of: “Total revenue in Q1 2026 was PLN 4.2 million, up 12% compared to Q1 2025. The central region accounted for the largest share, at 38%.”
With Copilot turned on, the narrative gets even richer – it uses Azure OpenAI to analyze every visual on the page and produce a full write-up with trends, comparisons, and anomalies. The text updates automatically every time a filter changes. You can read more about what Power BI can do on our product page.
Copilot in Power BI: A Genuine Step Change
If Power BI’s built-in AI features are an evolution, Copilot is the revolution. It’s an AI assistant integrated directly into Power BI that understands natural language and can carry out tasks that used to take an analyst hours.
What Is Copilot, and How Does It Streamline an Analyst’s Work?
Copilot for Power BI is an assistant built on Azure OpenAI — the same technology behind ChatGPT. The difference is that Copilot is connected directly to your data model and works within the context of your own reports. You can chat with it in a side panel: ask it to build a visual, summarize a dashboard, explain a trend, or generate a DAX measure.
How does Copilot work in practice? You say: “Build a report page with the monthly revenue trend, the top 5 products, and a breakdown by region” — and Copilot generates a complete page with charts, KPI cards, and filters. Building that report by hand would take 2–3 hours. Copilot does it in under 2 minutes.
Building Reports and DAX Measures from Prompts
One of Copilot’s most valuable uses is generating DAX measures from a plain-language description. DAX (Data Analysis Expressions) is Power BI’s formula language — powerful, but hard for many users to master. With Copilot, you can type: “calculate the average order value for customers who bought more than 3 times in the last quarter” — and get back a ready-made, correct formula.
Copilot can also automatically write descriptions for measures, which helps other users understand what a given formula is actually calculating without having to read the code. That matters a lot on teams where one person builds the reports and dozens of others use them.
Requirements and Availability – How Do You Turn Copilot On?
Copilot requires paid Microsoft Fabric AI capacity. Since April 2025, it’s been available on every paid SKU starting at F2 (roughly PLN 1,100/month in Poland) – a significant drop from the previous F64 minimum. One important thing to flag: the Power BI Premium Per User (PPU) license, at around PLN 85/user, does NOT include Copilot – that’s the most common licensing mistake we see.
Microsoft Fabric is the broader platform that Power BI is one component of, alongside Data Factory, Data Engineering, and Data Science. Turning on Copilot means assigning a workspace to Fabric capacity, which an administrator can do from the admin portal. Copilot is enabled by default – if you don’t see it, check your capacity settings and make sure you’re running the latest version.
Advanced AI Capabilities: Machine Learning for Power Users
For companies that want to go beyond the ready-made visuals, Power BI integrates with Azure services, making it possible to use advanced machine learning directly inside your reports.
Integration with Azure Cognitive Services and Azure Machine Learning
Power BI’s machine learning capabilities can be extended by connecting to Azure Cognitive Services. That makes it possible, for example, to run sentiment analysis on text – customer reviews, social media comments – directly inside Power BI, with no need to export the data to a separate tool.
The Azure Machine Learning integration also lets you plug in your own machine learning models – a predictive model trained on your company’s historical data, for example – and use it as a data source for a report. For manufacturing companies, that could mean forecasting material requirements based on order history and seasonality.
Anomaly Detection and Forecasting
Anomaly detection automatically flags data points that deviate significantly from the norm – an unexpected spike in shipping costs in a given week, for example. The system doesn’t just point out the anomaly; it also suggests possible causes by analyzing related dimensions.
Forecasting in Power BI lets you add a trend line and a future projection to any line chart with a single click. The algorithm accounts for seasonality, trend, and the variability of historical data. It’s a simple tool – it won’t replace an advanced ML model – but for many companies it’s enough for sales planning, budgeting, or inventory management. You can read more about how analytics supports manufacturers in our article on why ERP matters for modern manufacturing.
How to Roll Out AI in Your Reports: Practical Advice
Turning AI features on is one thing – but for them to deliver real value, you need solid foundations: clean data and a deliberate choice of tools.
Data Preparation: The Foundation of AI Success
No AI can draw meaningful conclusions from messy data. Cleaning your data in Power BI is the first step before rolling out any AI feature. That means removing duplicates, filling in missing values, standardizing formats (dates, currencies, names), and building a proper star schema with clearly named tables and columns.
For Copilot, the quality of your semantic model is critical — the better your tables, relationships, and measures are described, the more accurate the answers it generates. It’s worth investing the time to write a description for every measure and add synonyms to your columns (e.g. revenue = income = turnover) so Copilot understands the different ways people phrase the same question. You can read more about preparing your company for digital transformation in our article on ERP pre-implementation analysis.
Matching the Right Feature to the Business Problem
How do you use AI in Power BI effectively? The key is matching the tool to the business question. Want to know what’s driving a sales decline? Use Key Influencers. Need to trace an anomaly in costs back to its source? Reach for the Decomposition Tree. Need a forecast for next quarter? Turn on Forecasting. Want the system to write the report summary for the board on its own? Use Smart Narrative or Copilot.
The best way to roll out AI is to start with one concrete use case — automating the summary of your monthly sales report, for example — and only expand into other areas once you’ve validated the results. A “small step, big value” approach works far better than trying to automate everything at once.
Get the Full Value Out of Your Company’s Data
Turning on Copilot isn’t enough on its own. For AI in Power BI to give you accurate answers, it needs a clean data model, a logically structured set of reports, and a team that knows how to ask the right questions. The technology is ready. The question is whether your data is too.
At IT Vision, we combine analytics expertise with years of experience in Microsoft implementations. We help companies move from spreadsheets to intelligent dashboards — step by step, without forcing a revolution. As part of our work together, we offer:
- Power BI and Microsoft Fabric implementation — we’ll design the data model, build the reports, and configure Copilot to answer your management team’s questions, not ours.
- Integration with Dynamics 365 Business Central — reports fed live from your ERP data, with no manual exports or imports.
- Power BI and Copilot training — from the basics for new users to DAX workshops for analysts.
- Analytics support — when a new business question comes up, you don’t have to wait for the next project; we’ll extend your existing reports as part of a support subscription.
Book a free consultation — we’ll review your current reports and show you exactly where AI can save your team real time.
Frequently Asked Questions
Is Copilot in Power BI a paid feature?
Yes – Copilot requires paid Microsoft Fabric capacity (starting at SKU F2, roughly PLN 1,100/month in Poland). Power BI Pro and Premium Per User (PPU) licenses don’t include Copilot. It’s also worth remembering that the Fabric cost covers more than just Copilot – it’s the entire analytics platform, including Data Factory, Data Engineering, and other components.
Is my data safe when I use AI features?
Yes. Copilot runs within your organization’s own tenant. Your data isn’t used to train Microsoft’s AI models and never leaves your environment. Copilot’s answers are generated within the context of your own data model, respecting Row-Level Security (RLS) permissions.
Do I need to know English to use Q&A and Copilot?
Q&A has long supported multiple languages, including Polish – you can ask questions in your own language as long as your data model’s column names are in that language too. Copilot, on the other hand, currently works best in English, although Microsoft is gradually adding support for more languages. In practice, plenty of users take a mixed approach: a data model in their local language, with English-language prompts to Copilot.
Will AI replace data analysts?
No – AI is changing the analyst’s role, not eliminating it. Copilot takes over repetitive tasks (building reports, writing DAX, generating summaries), but interpreting business context, validating results, and making decisions stay firmly in human hands. You can read more about the role of technology in business in our article on AI and BI for business.
IT Vision is an experienced provider of ERP systems, BI solutions, and B2B platforms, operating on the market since 2000. The company has completed over 400 projects worldwide, supporting organizations in their digital transformation. IT Vision’s team of experts combines business and technological knowledge, delivering high-quality implementations based on Microsoft technologies.
