AI is a technology that operates within existing systems—systems that in highly-regulated, high risk The MOC risk assessment must evaluate how the AI system affects existing safety controls. Principle 2: Protect Operational Systems Isolate the hazard, then control the risks. These uncertainties create opportunities for emerging and novel risks. a shared risk with companies creating large language models and foundation models.

MOC Maturity Index Change can be (and often is) a significant source of new risk. This may be enough to pass an audit but is not enough to effectively manage the risks due to: asset, you need processes that are adequately scoped, have clear accountability, and that effectively manage risks process to know whether or not: (1) there is sufficient capacity to manage planned changes and (2) risks

these goals are ambiguous or ill-defined they contribute to wasted efforts and ultimately compliance risk Risk Risk is defined (ISO 31000, COSO) as the effects of uncertainty on objectives which involves having Reducible risk is treated by buying down uncertainty to improve the probability of meeting each objective Irreducible risk is treated by applying margin in the form of contingency, management reserve, buffers , insurance and other measures to mitigate the effects of the risk.

What is our risk appetite? What is our risk tolerance? Risk and Opportunity Register Risk Management Plan Risk-adjusted IMP 5. Measure progress. ​ (MoC) How will risk be measured? (MoR) How will assurance be measured? (MoA) Benefits realized Outcomes advanced Risk ameliorated Promises kept Obligations met If you are looking Rapid Improvement Engagements  (RIE) – Kaizens – to help you elevate your compliance and stay ahead of risk

Traditionally, GRC activities were centered around integrating the siloed functions of Governance , Risk Similarly, risk management was building risk registers and heat maps, and governance was providing oversight

) How best to improve compliance What level of investment to make What is at stake and the level of risk Regulatory Design Approaches Prescriptive-based (micro/means ) - rules that if followed will reduce risk Management-based (macro/means) - processes that must be followed to manage obligations and risk. organizations may elect to use a combination of the four regulatory designs based on the nature of the risks Compliance analysts should be aware of this when they identify obligations and evaluate compliance risk

The organization drifts outside the lines, remains blind to emerging risks, and loses sight of its mission forward begins with a foundational shift: organizations must take ownership of their obligations and the risks their obligations as personal commitments, not corporate procedures Leaders recognizing that compliance risk is operational risk, not a separate concern Executives accepting that audit findings represent their analyze some of your compliance gaps, generate your procedures, monitor your controls, and flag your risks—assuming

governing artificial intelligence (AI) in organizations, particularly within the context of compliance and risk brought both tremendous opportunities and risks to organizations. oversight; it requires proactive measures like "guardrails" (preventing harm) and "lampposts" (highlighting risks Why AI Is Different: AI presents unique risks because of its ability to operate with minimal human oversight Conclusion: AI governance is about keeping organizations "on mission, between the lines, and ahead of risk

stakeholder value, reputation, quality, and other value outcomes, a sea-change is happening to the risk regulators, standards bodies, and stakeholders recognize that to address more complex and systemic risk organizations need more latitude in terms of the means by which risk is addressed. This is a huge paradigm shift for this who work in risk and compliance. Substituting audit regimes with performance and risk-based compliance services has been slow although

additional uncertainty surrounding specific requirements that necessitate structured assurance and risk assurance and risk management activities in the context of safety. Assurance processes are not sufficient to handle risk Assurance entails the provision of quantifiable risks, and Establishing engineering margins for unavoidable or irreducible risk This distinction is By isolating AI-specific requirements and their associated assurance and risk needs, we can maintain

an OUTCOME not an ACTIVITY That's why confidence levels are an important measure of success for all risk is by having an operational compliance program to properly contend with obligation and operational risk resiliency, sustainability, quality, safety, diversity, or any of the abilities that contend with the risks

can make it difficult to understand how the AI system is making decisions and to identify potential risks It involves a range of activities, such as testing, verification, validation, and risk assessment, to Implementing Risk Management Strategies: Organizations need to develop risk management strategies to address the potential risks associated with the use of AI systems. This includes identifying potential risks, assessing the impact of those risks, and developing mitigation