As AI becomes embedded across the Microsoft Data Platform, from Copilot and Azure AI services to Microsoft Fabric, ethical considerations are now a practical responsibility for data professionals rather than a theoretical discussion. Decisions made during data preparation, modelling, and deployment directly affect fairness, transparency, and trust.

This session breaks down what AI ethics means in day-to-day data work and translates high-level principles into practical guidance for building AI-powered solutions on Azure and Fabric. It explores how issues such as bias, accountability, transparency, and privacy can emerge in real projects, often unintentionally, and how they can be addressed early in the solution lifecycle.

Using concrete examples, the session covers how bias can enter data models, governance considerations for AI features in Fabric and Power BI, and what Microsoft’s Responsible AI Standard means in practice when designing and deploying solutions. The focus is on helping attendees recognise ethical risks, ask the right questions, and make informed design choices.

By attending this session, you will:

-Learn how ethical risks arise in real-world data and AI solutions
-How bias can be introduced through data, modelling, and automation
-How to apply governance to AI features in Fabric and Power BI
-How Microsoft’s Responsible AI principles apply to real projects
-How to use a clear, actionable framework for evaluating AI features responsibly.

This session is aimed at data professionals who want to build AI solutions that are not only effective, but trustworthy, explainable, and aligned with real-world responsibilities.