Key Takeaways PII can enter AI systems through training datasets, fine-tuning data, RAG sources, and user prompts. Language models can memorize aspects of their training data, making it important to identify and protect unnecessary PII before training. Unstructured data such as documents, emails, support tickets, and scanned files can contain PII that is difficult to identify at scale. Data discovery, … Read More
POPIA vs. AI Act vs. LGPD vs. GLBA for US Businesses
Key Takeaways U.S. businesses may face international privacy laws depending on where they operate and process data. GLBA protects financial information handled by covered U.S. financial institutions. LGPD and POPIA regulate personal data in Brazil and South Africa. The EU AI Act regulates AI based on risk and can also apply to U.S. companies. Data visibility is fundamental to compliance, … Read More
Gartner Report: Why AI-Ready Data Requires Data Discovery
Key Takeaways AI performance depends on the quality, accessibility, and organization of the enterprise data it can access. Dark data becomes a greater risk as AI systems make hidden information easy to discover. Access controls cannot identify sensitive information hidden inside documents that users and AI systems can access. Sensitive data discovery, context-aware classification, and remediation should be part of … Read More
Use AI Without Violating Data Privacy Laws (2026 Guide)
2026 was supposed to be the “Year of the AI Agent,” where Large Language Models (LLMs) handle everything from corporate research to automated customer support. However, for many organizations, that promise has been stalled by a sobering technical truth: AI bots are data sponges. Whether your team is summarizing documents in ChatGPT, analyzing datasets in Copilot, or fine-tuning a proprietary … Read More
