Microsoft is putting Copilot at the center of Power BI, retiring legacy Q&A by December 2026.
Key takeaways
Trustworthy AI insights require Copilot-ready data models and strong governance controls.
Data literacy and AI upskilling are essential to turn Copilot into a strategic advantage.
The way business leaders interact with data is changing. In January 2026, Microsoft positioned Copilot, its generative artificial intelligence assistant, at the heart of Power BI, introducing capabilities that provide a more powerful, conversational analytics experience. At the same time, Microsoft confirmed it will fully retire the older Q&A visual in Power BI by December 2026. The message is clear: The future of business intelligence (BI) is AI-powered, and organizations must prepare.
For chief financial officers, chief operating officers and other senior leaders, this is more than a technology upgrade. It reframes how executives consume analytics, moving from static dashboards toward dynamic, on-demand conversations with data. However, realizing this promise requires a strong data foundation, robust governance and a workforce equipped to work alongside AI.
Why now: What’s changing in Power BI
Microsoft’s January 2026 updates introduced several key changes:
References may be attached to Copilot chats in the Power BI mobile app. Users can ask questions on the go and attach specific reports or datasets to Copilot chats as context to ground Copilot’s answers.
Stand-alone Copilot is available on the Power BI homepage. Users can start asking questions the moment they open Power BI, with the option to switch back to the classic dashboard view.
The “Prepped for AI” setting is updated to “Approved for Copilot.” Administrators can mark datasets as trusted for AI and restrict Copilot to using only vetted data sources, adding a critical governance layer.
Legacy Q&A will be retired. The Q&A visual and “Ask a question” tool will be fully deprecated by December 2026. Microsoft states that Copilot interprets questions and generates analysis more accurately and flexibly than Q&A.
Organizations currently using Q&A visuals or dialogs in dashboards should begin migration planning now, as these features will cease to function after the deprecation date.
What this means for business leaders
In the traditional BI model, executive engagement with analytics meant reviewing static reports or waiting for analysts to respond to ad hoc queries. Copilot changes this. For example, a CFO can open Power BI on a tablet and ask questions such as “What were our Q4 sales by region, and why were we off target in the West?” Copilot can then seamlessly produce a data-driven chart with a narrative highlighting the factors behind the shortfall. Business reviews shift from one-way presentations to two-way dialogues in which leaders probe the “why” in real time. This sets a new expectation: BI comes to the decision maker, not the other way around.
Your data foundation makes or breaks Copilot
However, Copilot does not fix messy or siloed data. Instead, it surfaces and amplifies underlying inconsistencies. RSM’s Middle Market AI Survey 2025 reinforces this: Among respondents who experienced AI implementation issues, 41% expressed concerns about data quality, the top problem companies faced. Organizations should curate a single source of truth for key metrics and dimensions, creating a governed semantic layer on which Copilot can confidently draw.
Designing Copilot-ready semantic models
Preparing for Copilot connects data governance, model design and business alignment. Key focus areas include:
- Consolidate into enterprise-wide models. Standardize metric definitions and naming conventions so an executive receives the same answer regardless of which report or team’s data is queried. Align data models with how business leaders actually think about operations.
- Use “Approved for Copilot” controls. Mark certified datasets as trusted for AI analysis. Administrators can limit AI access to only approved models, encouraging formal dataset certification before AI-driven use.
- Leverage prep data for AI features. Use Power BI’s built-in prep data for AI capabilities that allow you to further refine your semantic models through AI data schemas, AI instructions and verified answers.
- Plan your Q&A migration. Replace Q&A visuals with the Copilot pane in reports and the stand-alone Copilot experience on dashboards.
Establishing a Copilot governance framework
CFOs responsible for reporting integrity and risk management are increasingly taking active roles in AI governance. CFOs are working more closely with chief information officers and chief information security officers to put guardrails around AI and data usage.
A Copilot governance framework should address:
Data access controls
Establish role-based policies that define which user groups can query certain data via Copilot.
AI output monitoring
Track AI-generated questions and responses for auditing and accountability.
Dataset certification
Use “Approved for Copilot” to limit AI to vetted, high-quality sources.
Responsible AI alignment
Align approval workflows and guardrails with the organization’s responsible AI principles.
These controls should align with broader enterprise data governance. These are the same principles RSM emphasizes in master data management: defining policies, processes and roles to ensure data is trusted, available, understood and compliant.
Building AI and data literacy
Technology alone is not enough. Microsoft’s research indicates 82% of business leaders believe employees need new skills like prompt engineering, critical thinking and AI oversight to work effectively alongside AI.
In practical terms, finance and operations teams must learn not only how to ask Copilot a question, but also how to interpret and validate AI-driven insights. Developing a strong data culture, where business users have both trust in the data and training to use AI tools, is just as important as adopting the technology itself.
The takeaway
Microsoft’s investment in Power BI’s Copilot capabilities and its decision to retire legacy Q&A by December 2026 signal a fundamental shift in how organizations interact with Power BI. For finance and operations leaders, this creates both an opportunity and an obligation—the opportunity to move from static dashboards to dynamic, conversational analytics, and the obligation to ensure the data, governance and human capabilities behind these tools are ready.
Organizations that proactively invest in Copilot-ready semantic models, governance frameworks and data literacy will be positioned to unlock trustworthy, explainable AI-generated insights. Those that delay will risk scrambling to meet the deadline while competitors are already having smarter conversations with their data.
Ready to get started? RSM’s experienced advisory team understands the enterprise AI journey and the foundational elements necessary to generate increased value and reduce risk. Contact our team to learn more about how Copilot readiness and AI-driven analytics can transform your key business operations.
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