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Why Traditional Data Security Needs a Rethink As enterprises scale Generative AI initiatives, they are creating an explosion of new data types, AI-generated reports, model outputs, chat interactions, and dynamic knowledge artifacts. This is not just “more” data. It is data that’s unstructured, fast-moving, distributed, and difficult to govern with traditional security methods. Legacy data security models were built for predictable, structured environments. Today’s hybrid, cloud-native enterprises operate in the opposite: high-velocity, multi-format, continuously shifting data ecosystems. This is where Data Security Posture Management (DSPM) comes in, a modern, contextual framework designed to secure data no matter where it lives or how it evolves. DSPM must level up for the GenAI era, as shadow AI usage, unpredictable model-driven data flows, and new attack surfaces demand security that is more intelligent, adaptive, and proactive. This blog explores how GenAI-augmented DSPM transforms static safeguards into real-time, autonomous data risk intelligence, empowering organizations to innovate without compromising security. What Is DSPM? Data Security Posture Management (DSPM) provides continuous visibility, risk assessment, and governance for data across hybrid and multi-cloud environments.Unlike perimeter models, DSPM gives contextual insights into: Core DSPM Capabilities Discovering Sensitive Data Finds structured, unstructured, and hidden/orphaned data across cloud services, SaaS apps, databases, and internal systems. Classifying & Tagging Data Applies labels for sensitivity, compliance, and business value, enabling better governance and access control. Prioritizing Exposure Risk Evaluates risk through contextual cues, permissions, encryption, user behavior, and misconfigurations. Enforcing Governance Policies Supports least-privilege controls, automated oversight, and policy-based management. Real-Time Monitoring Tracks changes to data posture, permissions, and compliance continuously, shifting from reactive to proactive security. The GenAI Disruption: A New Security Dynamic Generative AI brings transformative productivity, but also introduces unprecedented data risks that traditional DSPM alone cannot handle. Key Challenges in the GenAI Era: Unstructured Data ExplosionGenAI produces massive volumes of text, audio, images, often sensitive but unclassified. Shadow AI UsageEmployees using ChatGPT, Copilot, or unapproved AI tools may unknowingly expose confidential data. Prompt Injection & Model LeakagePoorly governed models can reveal sensitive information or be manipulated by attackers. These complexities require DSPM solutions that understand how data behaves inside AI-driven workflows, not just where it resides. These emerging risks highlight the need for DSPM enhanced by GenAI, capable of securing data across fast-moving AI workflows. How GenAI Supercharges DSPM GenAI does not replace DSPM, it transforms it. Here’s how AI elevates data security posture: Smarter Classification Across All FormatsGenAI identifies sensitive data inside PDFs, chat logs, images, voice transcripts, and other unstructured formats previously difficult to analyze. Context-Aware Risk ScoringAI dynamically scores risks based on behavioral anomalies, user roles, and data movement, reducing alert fatigue. AI-Driven RemediationRecommends or automates remediation actions such as access tightening, data isolation, or “what-if” simulations before applying policy changes. Conversational IntelligenceSecurity teams can quickly query DSPM for specific insights, such as externally shared datasets or users who accessed payroll data last month, making data access faster and more intuitive.This accelerates investigation, collaboration, and decision-making. “GenAI turns DSPM into an intelligent command center, delivering