Ariel Evans is a senior cybersecurity and AI governance expert, serial entrepreneur, and award-winning author. She is CEO and Co-Founder of RiskQ Inc., a cyber risk quantification and AI governance platform, and founder of Cyber Intelligence 4U, an executive education and thought leadership initiative, where she has educated more than 5,000 global business leaders. She is the author of Managing Cyber Risk, Enterprise Cyber Risk in Digital Business and Navigating Supply Chain Cyber Risk.Ajay Singh is a globally recognized cybersecurity and AI governance expert, Professor of Practice, former Chief Executive Officer, and award-winning author. A Fellow of the Institute of Directors, he advises boards, governments, and regulators on enterprise cyber resilience and AI governance strategy. He has authored several internationally acclaimed books on cyber risk management, including Cyber Strong, an International Book Awards Finalist (2022).

• Section 1 The Importance of Definitions in AI. 1 Why Definitions Matter in AI. 2 AI Terminology and Definitions for Non-technical Readers. 3 Challenges in Defining AI Concepts. 4 The Future—Standardizing AI Definitions. Section 2 AI Regulations—A Global Overview. 5 Key AI Regulations and Frameworks. 6 Common Themes in AI Regulation. 7 Cybersecurity and AI Regulatory Use Cases. Section 3 AI and Governance—Balancing Innovation and Regulation. 8 Key Aspects of AI Governance. 9 AI Governance Framework Models. 10 Best Practices in AI Governance. 11 The Future of AI Governance. Section 4 AI and Cyber Controls—Strengthening Security and Mitigating Threats. 12 AI and Cybercrime. 13 AI in Cybersecurity. 14 Cyber Risks Posed by AI. 15 Cyber Security Controls for AI. 16 Control Frameworks for AI. 17 AI Risk Assessment Framework. 18 AI Applications in Business—From ChatGPT to Copilot: Cybersecurity Concerns. 19 The Future of AI Cybersecurity. Section 5 AI and Explainability—Understanding the Black Box. 20 Why Explainability Matters in AI. 21 Types of AI Explainability. 22 Challenges in Explainability. 23 Explainability Methods and Tools. 24 Regulations and Explainability Standards. 25 The Future of AI Explainability Section 6 AI and Privacy—Protecting Data in the Age of Intelligent Systems. 26 Data Collection and Consent in AI Systems. 27 Data Security and Anonymization. 28 Surveillance and Ethical Considerations. 29 AI and User Control. 30 AI in Social Media and Advertising. 31 Emerging Solutions for Trustworthy AI. Section 7 Organizational Alignment. 32 The Role of the Chief Technology Officer in Cybersecurity and AI. 33 Cybersecurity and AI Legal Team Roles. 34 The Role of IT Governance and the Chief Data Officer in AI. 35 The Role of the Cyber Team. 36 Cybersecurity and AI Roles in the Evolving IT Landscape. 37 Cybersecurity and AI Compliance Team Roles. 38 The Role of the CPO and Privacy Team. 39 Cybersecurity and AI Project Management Roles. 40 AI in HR and Training. 41 From Principles to Practice—The Enterprise AI Governance Playbook

'Artificial intelligence is no longer a future consideration—it is a present-day governance, risk, and leadership challenge. This book provides a clear, disciplined framework for understanding how AI reshapes cybersecurity, enterprise risk, and regulatory accountability. What makes this work stand out is its practical grounding: it connects strategy to execution, and innovation to responsibility. For executives, board members, and policymakers seeking to deploy AI with confidence rather than optimism alone, this book is an essential guide.'Dr. Yoav Intrator, Former CEO, JPMorgan Chase Israel'AI has pervaded all industry sectors, and businesses face a multitude of challenges when implementing it. AI Governance: The Executive Handbook for Safe and Responsible AI uniquely equips readers to integrate AI safely, with real‑life guidance from top executives on overcoming regulatory, governance, cybersecurity, and risk challenges.' Dr. Shariq Nisar, Fellow at the Harvard Law School and Distinguished Management Professor at the University of Luxembourg