What Else Is Microsoft Retiring? The Power BI Q&A Setup Tools Enterprise Teams Overlooked
- madhupandit
- 3 days ago
- 4 min read
Updated: 1 day ago
If you read our earlier post on Copilot for Power BI and the Q&A retirement, you already know that Power BI Q&A visuals will stop working entirely in December 2026. But there is a second part of the retirement announcement that received far less attention, and it affects enterprise teams that invested significant time and effort into making Q&A work well.
Microsoft is retiring the entire Q&A Setup.
What Is the Q&A Setup?
Most business users only ever saw the front end of Q&A, the search box where you could type a question and get a visual response. But behind that experience was a suite of configuration tools that report authors and BI teams used to make Q&A more accurate and more useful.
Q&A Setup included several components. Synonyms allowed report authors to teach Q&A that "revenue" and "turnover" meant the same thing, or that "headcount" referred to the employee count measure. Linguistic schema gave the model an understanding of how the organisation used language specific to its industry or internal terminology. Row labels helped Q&A understand what individual records represented — a "customer," a "product," a "transaction." Teach Q&A allowed authors to correct misinterpretations manually, building up a library of accurate responses over time. Review questions gave administrators visibility into what users were actually asking, so the model could be refined accordingly.
For organisations that used Q&A seriously, this configuration work represented a meaningful investment. It was the difference between Q&A producing unreliable or confusing results and Q&A actually being trusted by business users.
All of it is being retired in December 2026.
What Does This Mean in Practice?
For teams that never configured Q&A Setup, the impact of this part of the retirement is minimal. But for organisations that did invest in it, there are two distinct losses to account for.
The first is the tooling itself. The interfaces, the synonym libraries, the linguistic schemas, these will no longer exist in Power BI after retirement. Any configuration work completed in Q&A Setup cannot be directly migrated or exported in a way that carries across to Copilot automatically.
The second loss is subtler but equally important: the institutional knowledge embedded in that configuration. Over time, Q&A Setup accumulated an understanding of how a specific organisation used language: its terminology, its definitions, its naming conventions. That understanding lived inside Q&A Setup. When it goes, so does everything captured there.
This matters because the same challenge that Q&A Setup was designed to solve, making a natural language interface understand your organisation's specific language and data, still exists with Copilot. It has just moved to a new framework.
Introducing Prep Data for AI
Microsoft's replacement for Q&A Setup is called Prep Data for AI. It serves a similar purpose, helping report authors and BI teams configure their semantic models so that AI-powered natural language tools, including Copilot, work accurately and reliably. But the approach is different, and in most respects more rigorous.
Where Q&A Setup was primarily about teaching the model to understand language, Prep Data for AI is about ensuring the semantic model itself is structured in a way that AI can interpret correctly. The focus shifts upstream, from patching the natural language layer to building a model that is inherently AI-ready from the ground up.
We will cover Prep Data for AI in detail in our next post. But the important point for now is this: organisations that configured Q&A Setup cannot simply transfer that work across. The migration requires a structured reassessment of the semantic model, which is precisely what Prep Data for AI provides a framework for.
What Should Enterprise Teams Do Now?
There are three immediate priorities for any enterprise organisation that has used Q&A Setup.
First, audit what exists. Understand the extent of your Q&A Setup configuration: synonyms, linguistic schema, teach Q&A corrections, and row labels. Document what was built, even if it cannot be migrated directly. This documentation becomes an input into the Prep Data for AI process.
Second, assess the gap. Identify which of the business language and terminology captured in Q&A Setup is reflected in your semantic model's naming conventions and structure, and which exists only in the Setup layer. If your measures and fields are named clearly and consistently in the model itself, you are in a better position. If your model relied heavily on Q&A Setup to compensate for inconsistent naming, that technical debt now needs addressing at the model level.
Third, factor this into your Copilot readiness timeline. The December 2026 deadline applies equally to Q&A visuals and Q&A Setup. Organisations that have both in place have two parallel workstreams to manage, not one.
The Bigger Picture - Power BI Q&A Setup retirement
The Power BI Q&A Setup retirement is a signal, not just an inconvenience. Microsoft is consolidating its natural language capability into a single, AI-powered layer and the prerequisite for that layer working well is a semantic model that is clean, consistent, and structured with AI in mind.
Q&A Setup was a workaround for models that were not built that way. Prep Data for AI is the framework for building models that do not need workarounds.
That is a meaningful shift in how enterprise Power BI environments need to be designed and maintained going forward. The organisations that understand this early and act on it will have a Copilot experience that delivers on its promise. Those that do not will find that Copilot underperforms regardless of how much capacity they invest in.
In our next post, we look at exactly what Prep Data for AI involves and what enterprise teams need to do to get their semantic models genuinely ready for AI.
If you would like to understand the extent of your Q&A Setup investment and what it means for your Copilot transition, book a discovery call with Luminova Analytics. We will give you a clear picture of where you stand and what needs to happen before December 2026.
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