Trump’s America’s AI Action Plan
The U.S. unveiled a sweeping new AI strategy this week. Trump’s AI Action Plan marks a major shift in federal policy with global implications.
The EU AI Act 2025: A Turning Point in AI Regulation
The EU AI Act, now in phased implementation through 2027, introduces a risk-based regulatory framework for artificial intelligence, setting strict compliance rules for high-risk systems and general-purpose AI across the European Union.
Shadow AI in the Workplace
Shadow AI refers to the unsanctioned use of AI tools by employees without organizational oversight. This article explores the risks it poses to compliance and data protection, and provides practical steps to detect and govern its use responsibly—ensuring alignment with the GDPR, the EU AI Act, and internal policies.
AI Persona Rights: Who Owns Your Digital Clone?
AI personas are revolutionizing identity in the digital age—but at what cost? This article explores the legal, privacy, and ethical risks of cloning your voice, face, or personality. From unclear ownership rights to data misuse, learn why protecting your digital self has never been more critical.
Updating Policies for AI Privacy and Security
AI introduces privacy and security risks traditional policies can’t handle. This article explains how to update your policies to address AI-specific challenges, from re-identification and model attacks to compliance with the EU AI Act and NIST guidelines.
AI Act Update: GPAI Code of Practice Not Finalized
As of May 2, 2025, the EU has not finalized its General-Purpose AI Code of Practice, a key milestone under the AI Act. While the European Commission promises publication before August, the delay reflects mounting tensions between regulation, industry lobbying, and international pressure in shaping AI governance across the EU.
Innovation Regulation in AI Governance
In AI governance, innovation and regulation often collide. While rapid development drives progress, regulatory frameworks demand caution, clarity, and control. This article explores the Innovation Regulation Paradox—how the push for speed can be hindered by compliance needs. It offers strategies for integrating governance into development, enabling responsible innovation without sacrificing agility. The final piece in our paradox series.
Solving the Data Paradox in AI Governance
AI systems require vast datasets to perform effectively, yet privacy laws demand minimization, purpose limitation, and short retention. This article explores how organizations can reconcile these conflicting imperatives—balancing legal compliance with technical performance—through strategic governance, privacy-preserving techniques, and proactive design principles that embed ethical data use into AI development.
The Global Local Regulatory Paradox in AI Governance
AI systems are global, but the laws that govern them are local. The Global Local Regulatory Paradox explores the compliance challenges this creates—and how organizations can build adaptive governance frameworks to manage fragmented regulatory demands across jurisdictions.