Practical AI Governance

Building a Program for Strategy and Oversight
1. Auflage 2026
ISBN: 978-1-3986-2620-1
Verlag: Kogan Page Ltd

Buch, Englisch, 296 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 666 g

Organizations of all sizes are increasing their investment in AI products, tools and developments. However, these transformative technologies come with significant risks and challenges. This actionable guide builds scalable and practical AI governance program that encourages innovation and minimizes risks.

Practical AI Governance will show senior AI, tech and businesses leaders how to design an AI governance program built on proactive engagement, centralized intelligence and adaptive governance, all driven by continuous monitoring. Providing a strategic oversight structure to evaluate and implement AI governance, the book covers the building blocks to creating an AI governance program, the necessary structures and tools for oversight and how to future proof an organization's efforts.

Suitable for any business, this book will demonstrate how to align AI strategies with the needs of multiple stakeholders, the changing regulatory environment, technological trends and an organization's innovation and risk appetite. It explains how to embed AI governance in existing cybersecurity and risk management frameworks and scale AI governance across an organization. Going beyond traditional compliance checklists, it instead offers a logical and holistic approach to governance.

Autoren/Hrsg.

Rosenberg, Shoshana

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensorganisation, Corporate Responsibility Unternehmenskultur, Corporate Governance
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Wirtschaftswissenschaften Betriebswirtschaft Management Unternehmensorganisation & Entwicklungsstrategien
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensorganisation, Corporate Responsibility Unternehmensethik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme

Inhaltsverzeichnis

Section - ONE: Foundations of holistic AI governance; Chapter - 01: The AI governance imperative; Chapter - 02: Understanding the AI governance ecosystem; Chapter - 03: Data governance - the bedrock of AI governance; Chapter - 04: Governance as a cultural framework; Chapter - 05: AI foundations for governance: models, capabilities and trade-offs; Section - TWO: Strategic foundations - core building blocks for AI governance; Chapter - 06: The structural foundations of AI governance; Chapter - 07: Proactive engagement - ensuring AI governance reflects operational reality; Chapter - 08: Centralized intelligence - tracking AI and AI governance issues in one system; Chapter - 09: Adaptive governance - ensuring oversights evolves as AI expands; Chapter - 10: Continuous monitoring - tracking AI governance effectiveness at the program level; Section - THREE: Strategic oversights: PRISM as mechanism for building and evaluating AI governance; Chapter - 11: PRISM - a structured approach to building and evaluating AI governance; Section - FOUR: Operationalizing AI governance - structures, tools, and oversights mechanisms; Chapter - 12: Anchoring AI governance in organizational structures; Chapter - 13: Assessing data risks to govern AI use, development and deployment; Chapter - 14: Aligning AI governance with business strategy and risk appetite; Section - 15: Tracking AI-enabled tools, systems and vendor deployments; Chapter - 16: Implementing the AI intake process - governing AI from the start; Chapter - 17: AI governance policies, guidelines and enforcement mechanisms; Chapter - 18: Upskilling leadership and key staff for AI governance responsibilities; Chapter - 19: Incident response: structuring oversight for AI failures; Chapter - 20: Systems level continuing monitoring and adaptive AI governance; Section - FIVE: Scaling and future-proofing AI governance; Chapter - 21: Scaling AI governance across business units and global operations; Chapter - 22: Measuring AI governance effectiveness and maturity; Chapter - 23: Preparing for regulatory evolution and multi-jurisdictional compliance; Chapter - 24: Integrating AI governance with enterprise risk and cybersecurity programs; Chapter - 25: Future-proofing AI governance against emerging technologies and risks

Über Autor(innen)

Rosenberg, Shoshana
Shoshana Rosenberg is an experienced AI governance thought leader and practitioner. She is the Chief AI Governance and Privacy Officer at WSP. She is the co-founder of the organization Women in AI Governance which works to advance equity in AI policy and leadership and is the founder of SafePorter, an award-winning SaaS data minimization solution. Shoshana Rosenberg is an advisor to the Institute of Operational Privacy by Design and is based in New York, NY.