Sensitive data, including account numbers, financial records, and medical information, is increasingly flowing through AI systems, while security and privacy have not kept pace. This has become one of enterprise AI’s biggest challenges today: how to use valuable data without exposing it. Jeremy Samuelson, Chief Technology Officer at Integrated Quantum Technologies (IQT), says companies don’t have to choose between performance and privacy. AI models process these representations rather than the original data, reducing unnecessary data exposure while maintaining model performance (speed, accuracy, and scalability). To address this, IQT has initiated the patent process for MASQ (Machine Action Security Quotient), a governance and security architecture for AI agents and autonomous AI systems.