AI arriving in the value chain, in the products organisations make, in their suppliers' processes, and On September 14 we take the next step: what compliance needs to do to prepare for AI, and what that means That work anticipated exactly what AI now demands. Real-time regulation. Promises kept by systems. That is what creates the opportunity now — to apply them to a world with AI. Open to everyone, so bring a colleague if they are interested in how to prepare compliance for AI.

I just attended a webinar from a leading GRC vendor promoting continuous risk assessment for AI. What I heard : AI introduces significant risk across organizations and within every functional silo. The bottom line : This was traditional (and basic) risk management applied to AI—and done poorly.  The promise of continuous risk assessment tied to AI was not delivered. ⚡  What AI Risk Actually Requires If this represents the best that GRC can offer for AI, we're in deep trouble.

AI is now collapsing those layers. agents, AI systems, and AI-powered applications actually operating between the lines? Bespoke, AI-generated solutions invert that model. That build operational visibility into their AI systems. He serves on ISO’s ESG working group, OSPE’s AI in Engineering committee, and chairs the AI Committee

Most conversations about AI and compliance go one of two ways. And AI is entering the compliance function itself. AI is what pushes them past what they can carry. What AI actually asks of you AI does not just add obligations to your list. This is the culture that can respond to AI. The bounded-set culture cannot.

This reality—that AI inherently lacks the capacity to care about its impacts—places a real and immediate As AI technologies transform modern businesses the obligation of “duty of care" has surfaced as a critical This duty represents the specific obligations that fall to organizations that integrate AI into their Organizations deploying AI face a critical choice today: Will you embrace your duty of care, or risk Take these essential steps now: ⚡️ Identify and evaluate AI obligations and commitments (regulatory,

Why do we think that paper AI policies will be enough to handle AI risk? With AI’s ability to learn and adapt, we need measures that are also able to learn and adapt. That’s why a static, paper-based policy will never be enough to govern (i.e. regulate) the use of AI. Governance – the means of regulation – must be as capable as AI.

accepting that audit findings represent their management failures, not their auditors' discoveries What AI Cannot Do And if you thought AI can help you with this, you will be left wanting. Here's the thing: AI cannot take ownership of your obligations. AI might be able to analyze some of your compliance gaps, generate your procedures, monitor your controls They'll add AI tools to the stack, automate the busywork, and still fail to keep their promises because

AI Safety Labels There is an idea floating around the internet and within some regulatory bodies that we should apply safety labels to AI systems, akin to pharmaceutical prescriptions. While well intended this is misguided for a variety of reasons, namely AI’s adaptive nature.   In contrast, AI systems represent a new paradigm of adaptive intelligence. An AI Regulatory Framework: Intelligent Compliance Laws of AI Regulation for Compliance Cybernetics pioneer

Most current thinking places AI at the monitoring or response layer: detecting anomalies, flagging incidents develops this as a formal proposal: **Promise Agents** — security equipment with embedded, fine-tuned AI finished design, but a direction worth examining for security architects, compliance practitioners, AI He serves on ISO's ESG working group and OSPE's AI in Engineering committee, and chairs the AI Committee

When it comes to AI, many don’t want to hear about the risk. Some will go as far as claiming that AI creates no threat to humans or the world we live in. They say, it’s only people that use AI, who create the risk. AI technologies and its interactions with systems. AI can provide great benefits, however, it also brings with it significant risk.

. ❤️ C1 — AI safety and Responsible AI in practice. It creates what's not there: safety, security, sustainability, quality, responsible AI, legal adherence

Unlike the commoditized world of cloud computing and agile development, AI systems need real engineering engineering as the discipline that adapts engineering rigour to whatever digital paradigm emerges: AI We stand at the threshold of the AI era. As a Professional Digital/AI Engineering Advocate, Raimund champions proper licensure across the entire He actively contributes to the profession through his leadership roles, serving as AI Committee Chair