In a recent interview, Todd Moore, global vice president of data security at Thales, emphasized the growing challenge of data risk amid the rapid adoption of artificial intelligence (AI) technologies. With over 90% of newly generated data being unstructured, primarily from AI systems, organizations face difficulties in ensuring data visibility, classification, and control across hybrid environments. Moore stressed the necessity of securing data throughout the AI life cycle—starting from creation to model training and outputs—to mitigate risks like data leakage and regulatory violations. He highlighted the concept of “Shadow AI,” where unmonitored AI operates across systems, making security controls essential. Moore outlined strategies for managing unstructured AI-generated data, including discovery, classification, and encryption. He also predicted that agentic AI and quantum computing would transform security frameworks by 2026. Continuous monitoring and governance over sensitive data are crucial for organizations to protect their intellectual property effectively.
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