AI governance often breaks down when principles are not translated into operational criteria. Organizations adopt AI quickly, but many still struggle to assess which use cases are viable, how risk should be measured, where controls are needed, and how to demonstrate that decisions are accountable, traceable, and proportionate to the level of exposure. In practice, the challenge is rarely awareness. It is execution. My work focuses on helping organizations adopt AI in a disciplined way by connecting governance, risk, and business decision-making. I focus on the practical questions that matter in real environments. Which AI use cases are worth pursuing. Which ones create unacceptable exposure. How should threats, vulnerabilities, and impacts be assessed across AI, IT, investment, and business projects. How should risk be quantified. What controls are needed. What evidence should exist if the process is reviewed by internal audit, regulators, customers, or boards. I serve as AI GRC thought leader and Academic Director at IE Law School, where I work on AI governance, digital compliance, and quantitative risk. My background combines enterprise risk management, internal controls, financial and technology audit, model risk, cybersecurity, and AI governance across multinational organizations and regulated environments. The working tracks discussed here are designed for leaders and professionals who need structure, clarity, and practical methods. For executive teams and business leaders, I work on AI adoption, use case review, governance design, and prioritization. The goal is to assess opportunities without ignoring accountability, control requirements, or regulatory implications. For risk managers, data scientists, and control functions, I focus on AI risk exposure, quantitative risk methods, and structured analysis of threats, vulnerabilities, and impacts. This includes model risk, drift, adversarial threats, third-party exposure, operational dependency, and financial consequences. For organizations reviewing transformation, IT, or investment decisions, I support structured evaluation of risk-adjusted value, implementation exposure, control design, and decision evidence. I also work with professionals building careers in AI governance, risk, compliance, and digital control functions, with a focus on practical positioning, executive communication, and capability development. The emphasis is always the same. Clear methods. Defensible decisions. Better adoption of AI and technology under real-world constraints. If your goal is to approach AI, IT, or strategic projects with stronger discipline, measurable exposure analysis, and better governance, you are welcome to book a session.