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Explore how tokenization can secure sensitive data in AI workloads while preserving analytical value in this 40-minute conference presentation from AWS re:Invent 2025. Discover strategies to overcome the common enterprise challenge of withholding sensitive data from AI models due to security risks, which often limits valuable business insights. Learn how tokenization renders data useless to unauthorized access and potential exposure while maintaining its utility for AI training and response generation. Gain practical insights from Capital One's large-scale tokenization implementation, including real-world architectural patterns, actionable strategies, and implementation blueprints specifically designed for complex AWS environments. Acquire comprehensive guidance for securing diverse AI-driven use cases at enterprise scale, with focus on both training data protection and response data security. Understand how to balance data security requirements with the need for meaningful AI-powered business insights across various organizational contexts.
