Aaron Simon

Trust in AI is becoming a defining factor for insurers as they integrate advanced technologies across underwriting, claims, and customer engagement. This panel will explore the critical question: how can insurers implement AI responsibly while maintaining confidence among customers, regulators, and internal stakeholders? By bringing together leaders from across the insurance ecosystem, the discussion will highlight practical approaches to AI governance, transparency, and risk management, emphasizing the importance of a multi-stakeholder perspective. Participants will gain insights into not just the “how” of deploying AI, but the “why” behind building trust and accountability in these systems. Panelists will share real-world strategies and lessons learned to ensure AI initiatives are ethical, compliant, and customer-centric. They will explore the frameworks, policies, and cross-functional collaborations that help organizations navigate regulatory expectations, mitigate biases, and maintain credibility in an AI-driven environment. Attendees will leave with actionable ideas for integrating AI governance into everyday operations, ensuring technology strengthens rather than erodes stakeholder confidence. Takeaways from this session will include how to:

• Establish governance frameworks that balance innovation with accountability
• Identify and mitigate potential biases in AI models
• Engage internal and external stakeholders to build transparency
• Align AI deployment with regulatory and ethical standards
• Foster an organizational culture that supports responsible AI use

Artificial Intelligence is transforming insurance at breakneck speed, but many leaders feel they’re flying blind when it comes to understanding whether their AI systems are actually working as intended. Aaron Simon, Campaign Planning & Analytics Manager at CSAA Insurance Group, will bring his expertise in leading Independent Model Validation, where he has developed frameworks for validating everything from catastrophe models to generative AI applications. In bridging the gap between technical model validation and business strategy, he has helped organizations adopt AI responsibly while maintaining competitive advantage. This presentation cuts through the technical jargon to provide insurance executives with a clear roadmap for implementing effective AI model validation programs. Get inspired with insights into quick wins for organizations starting their validation journey, common pitfalls and how to avoid them, future-proofing your program in light of emerging AI technologies and validation challenges, and more. You will leave this session ready to:

• Improve AI model validation
• Communicate model risk to boards and regulators
• Make AI investment decisions with confidence
• Measure validation effectiveness and ROI
• Continue the networking begun in this session with peers facing similar challenges