As companies speed up their use of AI and make data more available, the old ways of managing things—made for fixed separate systems—can't handle the changing risks complex rules, and needs of unorganized data. My session will present to data leaders practical new ways to manage things built on open data storage systems automated policies written as code, and AI-checkable compliance steps. Attendees will gain from my session real examples of technical plans and useful ways to bring together management for organized and unorganized data and AI models across different cloud setups. They will Find out how to make management ready for the future with standards that work together built-in security ideas, and flexible controls that grow with new ideas.

My session will focus on four main points:
1)Framework: A modular governance model integrating data, AI, and cloud security.

2)Case Study: Example of how to Implement an open lakehouse governance stack (Delta Lake + MLflow + Open Policy Agent).

3)Tools: Production code snippets used for policy automation, drift detection, and metadata lineage in a real-life business use case.

4)Action Plan: Prioritized steps on how they can modernize governance without stifling innovation in their respective organizations.