Artificial Intelligence Governance Professional (AIGP) Certification Guide

Prepare for the AIGP exam with a practical guide to AI governance, responsible AI, risk management, EU AI Act compliance, lifecycle controls, audits, trusted deployment, vendor oversight, and certification-ready conceptsKey FeaturesPrepare for the AIGP exam with focused coverage of AI governance, risk, and responsible AIApply EU AI Act, NIST AI RMF, ISO standards, audits, impact assessments, and lifecycle controlsUse checklists and scenarios to govern generative AI, RAG, vendors, and model deploymentBook DescriptionAI governance is now a priority for organizations adopting machine learning, generative AI, RAG, and agentic AI systems. Professionals preparing for the Artificial Intelligence Governance Professional (AIGP) exam need more than definitions; they need a way to connect certification domains with governance work. Artificial Intelligence Governance Professional turns AIGP preparation into a structured book journey for readers across privacy, compliance, legal, risk, security, product, policy, data, and technology roles. You will begin with AI fundamentals, model types, system classification, the AI lifecycle, responsible AI principles, and governance roles. The book then explains how to identify AI harms, assess bias, privacy, security, operational, and business risks, and apply controls such as documentation, human oversight, testing, monitoring, impact assessments, incident response, and audit evidence. As you progress, you will build exam-ready and workplace-ready knowledge of risk tiering, engagement, policy ownership, lifecycle checkpoints, validation, vendor due diligence, disclosures, and drift monitoring. You will also explore the EU AI Act, global AI laws, OECD principles, NIST AI RMF, and ISO AI standards. By the end, you will be prepared for the AIGP exam and confident in applying AI governance frameworks at work. What you will learnExplain AI systems, model types, lifecycle stages, and AIGP governance terminologyIdentify AI harms, affected parties, bias, privacy risk, security issues, and misuseApply responsible AI principles through oversight, documentation, testing, and controlsBuild risk workflows using probability, severity, impact assessments, and risk tieringInterpret NIST AI RMF, OECD principles, ISO standards, and EU AI Act obligationsGovern AI vendors, deployment, audits, drift risks, and prepare for the AIGP examWho this book is forThis book is for professionals preparing for the Artificial Intelligence Governance Professional (AIGP) certification and for those responsible for AI governance in practice. It is also useful for data scientists, AI engineers, business leaders, policy teams, consultants, and public sector professionals who must evaluate, approve, deploy, or monitor AI systems responsibly. No prior AI governance experience is required, although a basic understanding of AI, business operations, privacy, compliance, or technology projects will help readers apply the frameworks faster.