Enterprise-Compliant AI: Balancing Innovation and Security with Azure AI Foundry, Purview & Defender

In this session, we explore how enterprises can accelerate AI adoption while staying secure and compliant. We’ll showcase a blueprint for building and deploying AI solutions in alignment with regulatory frameworks like the EU AI Act. Learn how Azure AI Foundry helps innovate responsibly, Purview ensures data governance, and Microsoft Defender safeguards your AI environment.

Join this session to gain actionable insights into creating compliant, secure, and trustworthy AI systems that scale seamlessly in enterprise environments.

Learn how to accelerate AI innovation while staying compliant and secure.
Understand how Azure AI Foundry supports scalable, enterprise-grade AI.
Gain practical strategies for integrating Purview and Defender into your AI workflows.
Discover tools and techniques to prepare for emerging AI regulations like the EU AI Act.

Agenda/Outline
1. Introduction
Quick overview: The challenge of balancing innovation with compliance and security in enterprise AI.
Why AI solutions need to adhere to emerging regulations like the EU AI Act.
2. Azure AI Foundry: Innovation Without Compromise
Overview of Azure AI Foundry: building, deploying, and managing AI models at scale.
Use case: Building production-ready AI copilots with governance in mind.
Integration with Azure AI Studio for development and lifecycle management.
3. Microsoft Purview: Data Governance & AI Compliance
Ensuring compliant and trustworthy data usage with Purview.
Demonstrating data lineage, sensitivity labeling, and policy enforcement.
Purview + AI Foundry: How to trace, govern, and audit AI pipelines.
4. Microsoft Defender: Securing the AI Lifecycle
Overview of Microsoft Defender for Cloud and its role in AI security.
Threat detection for AI systems: Monitoring datasets, models, and APIs.
Proactive risk management and incident response for enterprise AI environments.
5. Putting It Together: A Compliance-Ready AI Blueprint
Step-by-step approach to building AI solutions & governance with Foundry, Purview, and Defender.
Real-world scenarios: EU AI Act readiness and enterprise implementation.
6. Q&A and Discussion
Interactive Q&A to address audience challenges and explore use cases.

Ask Me Anything: AI, Copilot, Azure, DevOps

Come with your questions and get them answered by the experts. If you are lucky, you might get a swag !

Microsoft's collaboration with Hugging face

In this session, I take you on a chronological journey through the groundbreaking collaboration between Microsoft and Hugging Face, and its transformative impact on AI and Machine Learning.

We’ll start by exploring the origins of the partnership, which began with the development of Hugging Face Endpoints, a machine learning inference service underpinned by Azure ML Managed Endpoint.
This initial collaboration set the stage for a series of innovative developments that have revolutionized the AI landscape.

Next, we’ll delve into the launch of the Hugging Face Model Catalog on Azure. This catalog, filled with thousands of popular Transformers models from the Hugging Face Hub, is directly available within Azure Machine Learning Studio.
I will highlight how this integration allows users to deploy Hugging Face models on managed endpoints, running on secure and scalable Azure infrastructure.

We’ll then discuss the challenges faced in deploying Transformers to production and how this collaboration has addressed these issues.
We’ll highlight how the partnership has simplified the deployment process of large language models and provided a secure and scalable environment for real-time inferencing.

Finally, we’ll explore the future of this collaboration and its implications for the AI industry. We’ll discuss how the integration of Hugging Face’s open-source models into Azure Machine Learning represents Microsoft’s commitment to empowering developers with industry-leading AI tools.

Takeaways:
- Understanding of the Microsoft and Hugging Face collaboration and its impact on AI and Machine Learning.
- Insights into the features and benefits of the Hugging Face Model Catalog on Azure.
- Knowledge of the challenges and solutions in deploying Transformers to production.

Join and discover how this collaboration is shaping the future of AI and Machine Learning.

How to Ensure Microsoft GenAI Solutions are Both Responsible and Compliant to the EU AI Act

Description: As generative AI (GenAI) continues to revolutionize industries, ensuring that these solutions are responsible and compliant with regulatory frameworks like the EU AI Act is paramount. In this session, Emilie Lundblad Director of AI & Automation at Hempel, will explore how to build and deploy GenAI applications that align with both responsible AI principles and the stringent requirements of the EU AI Act. Attendees will gain insight into the operationalization of responsible AI through Microsoft's trusted framework and learn best practices for addressing compliance challenges in high-risk AI scenarios.

The session will cover:
- An overview of generative AI and its transformative role in business.
- Key provisions of the EU AI Act, including high-risk AI classifications and prohibited practices.
- Microsoft's approach to responsible AI, ensuring fairness, transparency, and accountability.
- Real-world examples of compliant GenAI implementations in Microsoft Copilot and Azure AI.
- Best practices and steps for aligning AI solutions with the EU AI Act's requirements.

Also booked for DrivingIT in Denemark in November