Responsible AI¶
Explore labs, session repositories, and additional resources from Microsoft Build 2026 focused on responsible AI practices, including safety, governance, compliance, and observability for AI systems.
Session Repositories¶
| Session | Presenters | Repo | Session Page |
|---|---|---|---|
| From observability to ROI for AI agents on any framework | Sebastian Kohlmeier, Filisha Shah, Vivek Bhadauria | Repo | BRK252 |
| Any agent, any cloud: Standardized tracing with Foundry+OpenTelemetry | Hanchi Wang, Nagkumar Arkalgud | Repo | DEM341 |
| Observe, optimize and protect your hosted agents in Microsoft Foundry | Nitya Narasimhan, Filisha Shah | Repo | LAB540 |
📚 Additional Resources¶
AI Governance and Compliance¶
- Responsible AI principles - Microsoft's core AI safety and fairness principles.
- Governance of AI applications - Policy, auditing, and compliance frameworks for AI systems.
- Governing open-source AI models - Licensing, compliance, and responsible use of foundation models.
Safety and Observability¶
- Observability for AI systems - Tracing, monitoring, and diagnostics for agent behavior and performance.
- Azure AI Content Safety - Detecting harmful content and moderating AI outputs.
- AI safety and abuse prevention - Safeguards for production AI applications.
Frameworks and Integration¶
- Microsoft Foundry tools and integrations - End-to-end tooling for building and monitoring responsible AI systems.
- OpenTelemetry for AI applications - Standard observability instrumentation for AI/ML workloads.
- Enterprise AI governance and deployment - Scaling AI responsibly across organizations.