In a Forbes Technology Council article, the CEO of Relyance AI explains why traditional, static data security and DSPM approaches are increasingly misaligned with modern AI-driven architectures. The piece argues that point-in-time scans and at-rest visibility were designed for environments where data moved slowly, leaving organizations exposed as data is continuously transformed, reused, and propagated across AI systems.
The article makes the case for AI-native security built on continuous data flow visibility, real-time policy enforcement, and end-to-end lineage from source code through AI inference. As regulatory scrutiny and trust requirements increase, the perspective positions continuous oversight not only as a security necessity, but as a business enabler that allows organizations to innovate while maintaining control, accountability, and confidence in AI systems.