AI Implementation Part 2: Building Responsible AI - Governance That Works

As AI adoption accelerates, organizations face increasing pressure to establish clear structures for responsibility, oversight, and decision-making. This webinar focuses on how to build practical AI governance that works in real organizational settings—not just on paper.

We unpack how to define roles and responsibilities across business units, IT, risk, and compliance, ensuring that AI initiatives are both innovative and controlled. You’ll learn how to embed AI governance into existing frameworks, rather than creating disconnected processes that slow teams down.

A key focus is on real-world challenges such as “shadow AI,” where employees independently adopt AI tools without formal approval. We explore how organizations can address this constructively, balancing flexibility with control. The session also highlights lessons from larger organizations that have already implemented AI operating models, showing how governance can act as a catalyst for innovation rather than a barrier.

Key takeaways

• Howto establish AI governance frameworks
• Rolesand responsibilities across business, IT, and risk
• IntegratingAI governance into existing models
• Designingpolicies, controls, and decision processes
• Managingshadow AI in organizations
• Makinggovernance a driver of innovation

Target audience

• Businessand technology leaders
• Enterprisearchitects
• Governancespecialists
• PMOand transformation professionals
• CIOs/ CTOs
• Senioradvisors

Speaker: Louise Mehl is an external consultant and has many years experience in practical implementation of regulations in the fields of technology, business and requrements.

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