Ready to move beyond pilots? In this fast‑paced, practitioner session, we’ll share how we successfully rolled out 20,000+ Microsoft 365 Copilot seats and enabled 90,000+ Copilot Chat users across multiple industries. What worked, what didn’t, and what we’d do again. You’ll learn a repeatable adoption strategy, how to stand up a high‑impact Champion Network, and how to build communications and training that people actually use. We’ll also open our playbook on measuring value: the signals, dashboards, and research methods that reveal both productivity gains and employee experience impact. Expect concrete artifacts (templates, formats, cadences), live walkthroughs, and the small details that make large‑scale adoption stick. All distilled into pragmatic steps you can apply the day you get back to work. Learning objectives / takeaways: 1) Champion Network, done right: a 5‑step approach to identify, onboard, mobilize, and sustain champions, plus roles (Champion vs. Ambassador) and rhythms that scale. 2) Adoption materials that engage: what to ship in weeks 0–4 (kickoff, “prompt of the week,” Q&A sessions, executive talking points), and how to keep momentum through week 12. 3) Measure value with confidence: a practical measurement stack combining M365 Admin Center Copilot usage, Viva Insights’ Copilot signals, training and community metrics, and short‑cycle surveys. 4) Field‑tested pitfalls to avoid: expectation management (the “valley of reality”), licensing waves, content readiness, and governance handshakes with IT.

AI can transform work and even save lives, but only if we deploy it responsibly. In this session, we’ll share real-world insights from rolling out Microsoft 365 Copilot and Copilot Chat at scale, and how we embedded Responsible AI principles to protect privacy, fairness, and mental health. We’ll explore why ethical design matters, how OpenAI and Microsoft implement safeguards (including suicide-prevention triggers), and what organizations must do to align with frameworks like the EU AI Act and ISO/IEC 42001. Expect practical guidance on risk assessments, governance models, and human-centric design patterns that balance innovation with empathy. We’ll also discuss emerging use cases in healthcare and mental health support and the ethical dilemmas they raise. Walk away with actionable steps to make AI a force for good in your enterprise. Learning objectives / takeaways: 1) Understand the ethical risk landscape: Bias, privacy, autonomy, and mental health implications of generative AI. 2) Apply Responsible AI frameworks: Microsoft’s six principles (Fairness, Reliability, Privacy, Inclusiveness, Transparency, Accountability) and Avanade’s control model. 3 Design for human well-being: How to integrate safeguards like crisis-response triggers and empathetic UX patterns. 4) Operationalize governance: Practical steps to comply with the EU AI Act and ISO 42001, plus internal policy alignment.