Microsoft Fabric and Power BI: The Most Important Updates from October 2026

AI agents that build Power BI reports, independently perform data engineering, and provide increasingly accurate answers to questions about business data. In October, Microsoft once again made significant progress with Fabric and Power BI. But what do these developments mean in practice? We discuss the most important updates and share our experiences and insights.

Agentic development: building faster, but not without a developer

One of the most interesting developments is the expanded support for agentic development in Power BI. With MCP servers and other AI integrations, developers can increasingly delegate tasks to AI assistants. These include setting up data models, writing DAX measures, and building and formatting reports.

In October, the Power BI Report Authoring Skill was expanded to support custom visuals and made generally available. This allows AI agents to add custom visualizations, connect them to data, format them, and validate them. As a result, more and more parts of a report can be developed automatically.

At Bitmetric, we use Claude through an MCP connection to create initial versions of Power BI solutions.

This saves a considerable amount of time. As one of our consultants puts it: “No more spending two days just getting the padding right on every page.”

The results are particularly impressive when quickly building a proof of concept. At the same time, we find that refining an initial version can sometimes take a surprising amount of time.

We previously wrote about the possibilities of MCP servers for Power BI. We are now seeing how this technology is changing day-to-day development work.

Our view: AI is taking over more and more hands-on development work. As a result, the developer’s role is shifting toward understanding business requirements, designing good data models, and evaluating results. That is precisely where the added value lies.

More information: Power BI October 2026 Feature Summary.

Fabric Data Agents: better answers start with better definitions

Microsoft has made advanced SQL and DAX generation for Fabric Data Agents generally available. This enables agents to better determine which tables, relationships, and calculations are needed to answer questions about business data.

This is an important improvement, because a technically correct query doesn’t necessarily produce the right business answer.

Suppose someone asks about revenue in Germany. What exactly do we mean by revenue? Does it include returns? Does it exclude certain suppliers? And which date determines the reporting period?

With the improved query generation, an agent can take this kind of context into account more effectively, provided that the information is available.

Our view: the semantic layer is becoming even more important. Business definitions must be clearly documented and properly maintained. We also recommend testing agents using historical data for which the correct answers are known. This allows you to verify that an agent not only gives convincing answers but also produces the correct figures.

More information: Advanced NL2SQL and advanced DAX generation.

Project Osmos: AI will also perform data engineering

With Project Osmos, Microsoft is introducing a new AI agent for data engineering in Fabric. At FabCon Europe 2026, we already saw how Microsoft is placing an increasing emphasis on AI within the data platform. Project Osmos is the next step in that development.

Instead of working out every step yourself, you describe the desired outcome. The agent can then explore the data, generate code, prepare pipelines, and perform checks.

This could significantly speed up development, but it also requires clear rules and safeguards.

One of our consultants puts forward a clear guiding principle:

“The agent may prepare the change, but must not implement it until explicit approval has been given.”

That approval must be based on a review of the generated code and validation results. Clear rules are also needed for access permissions, development and production environments, schema changes, monitoring, and error handling.

Our view: the more autonomous agents become, the more important it is to define in advance what they may and may not do. Automation without control is not progress.

More information: Introducing the data engineering agent for Fabric.

Capacity management: sometimes a failed refresh is good news

Not every interesting update revolves around AI.

Microsoft has improved surge protection for Power BI semantic models. This allows the system to intervene sooner when processing operations are at risk of exceeding configured capacity limits. The improvement is applied automatically, so you do not need to change any settings.

This may mean that a refresh is rejected sooner. But that is not necessarily a disadvantage.

A failed refresh is visible and can be investigated. Unexpectedly high capacity usage, on the other hand, can have financial consequences.

We also see frequent rejections as a useful signal: it may be time to optimize the data model or processing.

Our view: effective capacity monitoring is not only about performance, but also about predictable costs. Of course, it remains important to actively monitor refreshes.

More information: Power BI October 2026 Feature Summary.

Two technical changes to keep in mind

In addition to these developments, there are two changes that will have an immediate impact on some organizations.

Databricks: from ODBC to ADBC. The new connector for Power BI and Fabric is generally available. Microsoft expects existing functionality to remain available, but organizations that use Databricks as a data source would be wise to test the transition in good time.

More information: Databricks ADBC connector for Power BI and Microsoft Fabric

Fabric Data Agents in Microsoft Foundry. The existing integration through a custom tool was phased out on November 6, 2026. Developers who use this integration must switch to the new integration through Fabric IQ.

More information: Retiring the Fabric data agent custom tool in Microsoft Foundry

Our conclusion: value is shifting from building to understanding

October’s developments show how quickly Microsoft is integrating AI into Fabric and Power BI. Work that previously required manual development can increasingly be prepared or carried out by an agent.

This also changes where a BI specialist adds value.

An agent can write a DAX measure. But does it understand why an organization calculates revenue in a particular way? Does it know which data is reliable? And can it assess whether a dashboard actually helps people make better decisions?

Those questions will only become more important.

Our advice: make sure the foundation is sound before deploying AI broadly. Document business definitions, establish governance and set clear guidelines for the use of data and AI.

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