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Rebecca O’Kill

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Rebecca O’Kill

2

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Rebecca O'Kill is the Chief Data and Analytics Officer at AXIS. Prior to joining AXIS, Rebecca spent 16 years at Beazley where she held several roles increasing in leadership including Interim Chief Data Officer and Head of Actuarial Analytics.

Bio from: Big Data LDN 2025

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In a world where AI agents, complex workflows, and accelerating data demands are reshaping every enterprise, the challenge isn’t just managing data, it’s creating trusted context that connects people, processes, and technology. 

Join Rebecca O’Kill, Chief Data & Analytics Officer at Axis Capital, for an Honest No-BS conversation about how her team is transforming governance from a compliance checkbox into a strategic enabler of business value. 

Together, we’ll unpack: 

• Minimal Valuable Governance (MVG): why the old ivory tower “govern everything” mindset fails, and how focusing on just enough governance creates immediate business impact. 

• The ACTIVE framework, a practical approach for governance built on: Alignment, Clarity, Trust, Iterative, Value, Enablement 

• How Axis Capital is embedding governance across the organization by uniting the “front office” (what and why) with the “back office” (how). 

• Why context and knowledge are critical for the next era of agentic AI and multi-agent workflows, and how Axis is preparing for it today. 

By the end, you’ll see how Axis Capital is turning governance into a competitive advantage and why this approach is essential for any organization looking to thrive in a world of AI-driven automation and connected workflows. 

As enterprises race to unlock AI, many face barriers like poor metadata and weak governance. In this session, Rebecca O’Kill (CDAO of Axis Capital), Tim Gasper, and Juan Sequeda share how AI is not just the outcome of governance—it’s the incentive. Framing AI as the “carrot” motivates adoption of governance as a strategic enabler. Learn how AI-powered governance, data marketplaces, and knowledge graphs together provide context, drive smarter metadata, and enable impactful AI use cases like underwriting agents that require structured and unstructured data.