Anastasia Zygmantovich

When scaling AI governance across global organizations, leaders face a key decision: centralized or federated governance? This session will examine the advantages and challenges of both approaches, providing strategies to determine the optimal model for your organization’s size, complexity, and regulatory environment.

·       Comparing centralized and federated governance models for global AI deployment.

·       Building flexible frameworks that scale with organizational needs and regulations.

·       Implementing governance structures that ensure consistency while allowing for local autonomy.

As AI becomes embedded across business functions, translating Responsible AI principles into scalable, context-aware practice is an enterprise-wide challenge. Over the past year, Reckitt has evolved its Responsible AI governance model from a conceptual framework to a robust, human-centered process tailored to the company’s operational reality. In this session, Anastasia and Tomasz will walk through key milestones in Reckitt’s RAI journey, sharing practical insights into how risk is evaluated, scoped, and mitigated across diverse AI initiatives. Attendees will gain a clear view of how Reckitt has adapted its governance approach over time - and what others can take from that experience.

• Defining and adapting evaluation scopes based on AI system complexity and business context
• Embedding human-centered reflection into RAI processes to address real-world organizational needs
• Iterating governance models by learning from frontline challenges and cross-functional collaboration