Building Trustworthy AI: Practical Governance for Modern IT Teams

AI is quickly becoming part of everyday software development, data platforms, and business operations. While organizations are eager to adopt new AI capabilities, many struggle with questions around data quality, accountability, security, and oversight. Governance can help address these challenges, but only if it fits naturally into existing engineering and IT workflows.

This session explores practical approaches for governing AI without slowing innovation. We’ll discuss how organizations can use AI to automate routine governance tasks such as metadata management, documentation, data quality monitoring, and policy enforcement, while keeping people responsible for decisions that require context and judgment.

Drawing on research and implementation examples across multiple industries, the session examines how human-AI collaboration improves governance efficiency, increases confidence in data, and supports responsible AI adoption. We’ll also cover common implementation challenges, including balancing automation with oversight, establishing clear accountability, and integrating governance into modern development practices.

Attendees will leave with practical frameworks they can apply to build trusted AI systems, strengthen data governance, and support responsible AI adoption across software, data, and IT teams.