Protecting Enterprise AI Data in the Post-Quantum Era

As enterprises accelerate AI adoption, they are collecting, combining, and moving greater volumes of sensitive data across increasingly complex environments. This talk will examine post-quantum cryptography through a data-protection lens, exploring why organizations must consider not only how data is secured today, but how long that protection must remain effective. I will discuss the practical challenges enterprises face, including identifying high-value data, understanding where vulnerable cryptography is used, managing legacy systems, and evaluating vendor readiness. Attendees will learn how data classification, risk-based prioritization, small pilot initiatives, and crypto-agile design can support a realistic post-quantum roadmap. This session will help practitioners connect AI growth, long-term data exposure, and post-quantum preparation without requiring a deep background in quantum computing.