Unstructured and structured data now power AI-driven decision-making across regulated industries—but most governance programs were not designed for AI-scale access and automation.

As GenAI adoption accelerates, organizations need more than metadata visibility. They need intelligent, governed access to data that is secure, explainable, and compliant by design.

In this session, we’ll demonstrate how IBM delivers a fully managed data intelligence platform that unifies discovery, governance, quality, lineage, and AI-powered automation across hybrid and multi-cloud environments. A live demo will showcase GenAI capabilities including conversational data discovery, text-to-SQL for governance workflows, and MCP tools that provide standardized, secure access to enterprise data.

Attendees will see how teams can accelerate analytics and AI initiatives, automate governance tasks, and enable trusted AI interactions—all accessible through a governed Model Context Protocol (MCP) server that ensures consistent controls, full lineage transparency, and enterprise-grade policy enforcement.

Speaker:

Mike Grasselt, Senior Software Engineer, watsonx.data intelligence Data Quality, IBM

Mike is a Software Architect at IBM specializing in next-generation data quality for AI-driven enterprises. His work focuses on building intelligent and automated data quality capabilities in watsonx.data intelligence, including AI-assisted rule understanding, remediation agents, data contracts, and developer-centric data quality tooling.

Resource Links:

• Product Page: https://www.ibm.com/products/watsonx-data-intelligence
• Demo Library: https://www.ibm.com/products/watsonx-data-intelligence/demo-library