Artificial Intelligence Governance Professional (AIGP) Certification Guide: Prepare for the AIGP exam with AI governance, risk, compliance, and respon
暫譯: 人工智慧治理專業人士（AIGP）認證指南：以 AI 治理、風險、合規與責任準備 AIGP 考試

Prepare for the IAPP AIGP exam with a concise AI governance study guide: EU AI Act, NIST AI RMF, ISO 42001, and governing GenAI, RAG, and agentic AI.

Key Features:

- Prepare for the IAPP AIGP exam with focused coverage of all four AIGP exam domains

- Apply the EU AI Act, NIST AI RMF, ISO/IEC 42001, impact assessments, audits, and lifecycle controls

- Govern generative AI, RAG, agentic AI, and AI vendors through real-world governance scenarios

Book Description:

Prepare for the IAPP Artificial Intelligence Governance Professional (AIGP) exam and learn to govern AI systems in the real world. As organizations adopt generative AI, RAG, and agentic AI, AIGP candidates need to understand how governance decisions shape the entire AI lifecycle.

This concise AIGP study guide covers all four AIGP exam domains. You'll start with AI fundamentals, OECD system classification, and responsible AI principles, then learn to identify AI harms, assess bias, privacy, and security risks, and run risk assessments using the NIST AI Risk Management Framework. You'll also work through impact assessments, testing, data governance, and model cards.

As you progress, you'll govern AI in production through vendor risk management, drift monitoring, incident response, and audits, with dedicated guidance on deploying RAG safely and defending agentic AI against prompt injection. The book then covers the EU AI Act in depth, U.S. rules such as NYC Local Law 144 and Colorado's AI law, and ISO/IEC 42001 and 42005. Written for privacy, compliance, legal, risk, security, and product professionals, with no machine learning background required, this book prepares you to take the IAPP AIGP exam with confidence and apply AI governance at work.

What You Will Learn:

- Explain AI systems, model types, lifecycle stages, and AIGP governance terminology

- Identify AI harms, affected parties, bias, privacy risk, security issues, and misuse

- Apply responsible AI principles through oversight, documentation, testing, and controls

- Build risk workflows using probability, severity, impact assessments, and risk tiering

- Interpret NIST AI RMF, OECD principles, ISO standards, and EU AI Act obligations

- Govern AI vendors, deployment, audits, drift risks, and prepare for the AIGP exam

Who this book is for:

This 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.

Table of Contents

- Foundations of Artificial Intelligence and AI Governance

- AI Impacts on People and Responsible AI Principles

- Responsible AI Governance and Risk Management

- Governing AI Development

- Governing AI in Production

- The EU AI Act

- Other Laws and Standards Related to AI