Why AI Agents Need Privacy Guardrails Before They Go Mainstream

As autonomous AI agents move from prototypes to production, they introduce new risks around data leakage, context drift, and unauthorized actions. This article outlines why privacy guardrails—input filters, sandboxing, policy engines, output validation, and observability—are essential to building safe, trustworthy agentic systems, plus the metrics and architectures needed to test and maintain them at scale.