How systematic privacy governance becomes competitive advantage for AI deployment
EDPB guidance demonstrates how structured privacy governance approaches for LLM systems create competitive advantages while ensuring regulatory compliance.
Documenting AI risk with NIST's four functions
The NIST AI RMF shifts AI risk management from abstract principles to a structured, operational process...When AI is ubiquitous, trust matters. The RMF provides a tool for building that trust through continuous improvement.
How to Build AI Systems You Can Actually Defend
The shift to widespread AI requires a shift in approach: from reactive problem-solving to intentional design... The organizations that get ahead of this will be the ones that can prove their AI systems work as intended—and can be trusted accordingly.
LLMs don't store personal data like databases do, privacy expert argues
A new analysis from the Future of Privacy Forum questions assumptions about how Large Language Models handle personal data. Yeong Zee Kin, CEO of the…
AI Companies newest Prompt: Blocking State Legislation
As of August 21, 2025, major tech players—OpenAI, Meta, and Google—are ramping up efforts to block U.S. states from enacting AI regulations that could…
Delaware's new AI sandbox is more than a headline
Most AI regulation discussions feel abstract. But when the Delaware AI Commission greenlights a sandbox specifically for agentic AI in corporate gover…
AI regulatory sandboxes are an accelerator for responsible product building
AI regulatory sandboxes serve as catalysts for responsible product development. It's an exciting trend gaining global traction, as highlighted in…
Privacy by Design in the Age of LLMs: A Deep Dive into EDPB’s New Report
Privacy by Design in the Age of LLMs: A Deep Dive into EDPB’s New Report
