Artificial Intelligence in Power BI: How Copilot Is Changing Data Analysis

One of the most significant developments in business intelligence in recent years is the arrival of generative AI inside the leading BI platforms. Microsoft, which leads the market with Power BI, has built advanced AI capabilities into the platform under the name Copilot — and in doing so has changed the way organisations approach their data.

Until now, building a report or a dashboard in Power BI meant knowing the structure of the model, the DAX language and the principles of good visualisation. With Copilot, data analysis is gradually becoming a natural conversation: ask a question in plain language and Power BI produces a visualisation for you, explains a trend or suggests an insight — without a single line of code.

What does Copilot actually do inside Power BI?

Copilot acts as an AI layer that sits on top of the organisation’s existing data model and lets users address it in natural language — Hebrew or English — and receive answers grounded in the organisation’s real data rather than in general information from the internet. That distinction is critical: every insight presented rests on the data sources actually connected to Power BI, so the result stays accurate, current and relevant to the business.

Key capabilities available today

• Conversing with your data (natural-language Q&A) — instead of hunting for the right field in the data tree, you can simply ask “which were our strongest sales last quarter?” and get an immediate answer with a matching chart.
• Automatic report creation — Copilot can propose the structure of an entire report from a short description of the business need, including the visualisations best suited to the type of data.
• Report summaries (narrative) — instead of scanning dozens of charts, the user receives a short, clear written summary of the report’s main trends, in business language rather than technical language.
• Anomaly and insight detection — the AI continuously scans the data and flags deviations, unusual trends or correlations that were not obvious to the user.
• DAX writing assistance — for analysts and model developers, Copilot suggests and even writes DAX formulas from a free-text description, cutting development time significantly.

What does this mean for organisations?

The main benefit is accessibility. Until now, extracting a deep insight from the data required a dedicated analyst who knew both the model and the query language. Now a department manager, a salesperson or anyone else without a technical background can ask a question and get a data-driven answer within seconds. This does not remove the need for BI specialists — quite the opposite: it frees them from routine work and allows them to focus on building stronger models and on strategic analysis.

It is worth remembering that, as with any AI tool, the quality of the answers depends directly on the quality and cleanliness of the underlying data model. An organisation with a well-organised, well-maintained BI model will enjoy accurate, fast insights. An organisation with messy or poorly connected data will get partial or incorrect answers — which is why investing in solid data infrastructure remains the basic condition for success.

How to get started

Rolling out AI capabilities in Power BI properly requires a combination of the right licensing (Copilot is currently available mainly in Fabric environments and in certain Premium/Pro plans), a well-organised data model with clear field names, and a gradual process that teaches users how to phrase questions in a way that produces accurate results. Organisations that take a staged approach — a pilot with one team, lessons learned, then wider rollout — tend to see the business benefit far sooner.

In summary

The integration of artificial intelligence into Power BI is not a passing trend — it is the direction the entire BI world is heading. Organisations that build quality data infrastructure and adopt the new capabilities thoughtfully will gain a significant competitive advantage: faster decision-making, broader access to data across the workforce, and less dependence on a single analyst who holds all the knowledge. This is exactly the kind of journey we at DataCore guide organisations through — from establishing a solid data model to implementing the most advanced AI layers Microsoft has to offer.