Blog

Effective Strategies for AI Risk Management for Privacy and Compliance Teams

AI risk management is no longer theoretical. For privacy and compliance professionals, it requires practical controls to address bias, data privacy, model reliability, and accountability. This guide breaks down the key risks of AI systems and outlines how governance frameworks, explainable AI, and human oversight help organizations meet regulatory expectations while enabling responsible innovation.

Healthcare Privacy Risk Management in the Age of AI: A RadarFirst Perspective on Amazon One Medical’s Health AI Announcement

As AI powered tools like Amazon One Medical’s Health AI assistant enter the healthcare ecosystem, privacy and compliance leaders face a pivotal challenge. How do you unlock innovation while protecting patient trust and meeting HIPAA obligations. AI can improve access to care and patient engagement, but it also introduces new privacy risks tied to data access, inference, and governance. Healthcare organizations must take a proactive, risk based approach to ensure AI adoption strengthens compliance rather than complicates it.

Top 10 Privacy Incident Metrics Every Healthcare Provider Should Track in 2026

In 2026, healthcare privacy leaders will be judged not just on compliance, but on speed, consistency, and defensibility. This guide breaks down the 10 most critical privacy incident metrics every health system should track, based on real-world benchmarking data and insights from hundreds of privacy and compliance teams. Learn how the right metrics turn incident response into a measurable, trust-building advantage.

AI Governance for Financial Services. Turning Regulatory Risk into Operational Control.

AI is transforming lending, fraud detection, and underwriting, but it also introduces new forms of risk that traditional IT controls cannot address. This article breaks down the key AI risks facing financial institutions, including algorithmic bias, black-box decisioning, and model drift, and explains how governance, explainable AI, and continuous oversight can turn AI into a compliant and trustworthy business asset.

What Under Armour’s Data Breach Claims Reveal About Modern Privacy Incident Preparedness

Claims that 72 million Under Armour customer records were exposed highlight how quickly privacy incidents now surface publicly. This analysis explores what the incident reveals about detection gaps, breach communication, and why proactive privacy incident management is now essential for enterprise organizations.

AI Risk in 2026. What Enterprise Privacy and Compliance Teams Are Already Managing

As AI adoption accelerates, enterprise privacy and compliance teams are being asked to manage growing risk with limited resources. Governance has become essential to maintaining visibility, accountability, and control.