Success Starts with Secure Data: A Practical Guide for Enterprises

This white paper-style report highlights how enterprise AI initiatives depend on high-quality, secure data and warns that inadequate data security and governance (especially around unstructured data, RAG, vector databases, prompt injection, and non-human identities/agents) can introduce operational, compliance, and cybersecurity risks; it recommends a unified, proactive data security framework with centralized visibility and classification, real-time monitoring, automated policy enforcement, identity-aware controls, and multicloud support to enable trusted AI.