Explore the emerging AI risks businesses need to understand, from psychological dependence and automation bias to misinformation and AI governance.
Who is responsible for an AI's decisions--and its mistakes? Is it the company that built the AI or the customer using it? According to regulations, there' s one clear answer.
AI is outgrowing traditional GRC frameworks. How can you keep up? Safeshield discusses the current industry and next steps for AI GRC.
Is AI GRC certification worth it? The answer depends on where you are, what you want, and whether the certification is part of a bigger career plan.
Is it worth paying for a certification in AI GRC? The Safeshield team weighs in on what you can get out of free vs paid training, and which is best for you right now.
Want to break into AI GRC? We break down the skills and knowledge you need to get started
Is your AI governance model compliant? Here, we provide an AI Governance Maturity Model to give you a clear idea of where you are in the governance spectrum, and how to reach the next step.
When we’re dealing with AI, we have to change the way we look at data. Information might have been collected in line with GDPR, but often, businesses end up using previous data to feed AI models, or to improve existing tools or AI decision making.
AI broadens the idea of what personal data is. The assumption that anonymising data puts you outside of the range of GDPR is muddied by the adoption of AI.
This guide provides a practical approach to AI governance for small and mid-sized businesses. It helps SMEs manage AI risk and build trust without overengineering their processes.
A complete guide to AI risk assessment. Learn how to analyse AI systems, identify technical and ethical risks, prioritise controls, and build continuous oversight aligned with AI governance standards.
This roadmap provides a practical, structured guide for professionals who already understand the foundations of AI GRC and are ready to advance their skillset.
