Artificial intelligence and advanced analytics are now embedded in core financial decision-making. With that reliance comes heightened regulatory scrutiny, operational risk, and accountability at the executive level.Model Risk for Financial Leaders is a practical guide for finance executives, risk leaders, and audit stakeholders responsible for governing analytical and AI-driven models across regulated financial environments. The book translates technical model risk management conc...

AI ethics often fails not because principles are wrong, but because they are not operationalized. Operationalizing AI Ethics shows how organizations translate high-level ethical commitments into concrete product decisions, controls, and release criteria.Written for product managers and delivery leaders, this book bridges the gap between abstract ethics frameworks and day-to-day product development. It explains how ethical risks emerge during design, data selection, model developmen...

As artificial intelligence becomes a material business risk and strategic enabler, boards are increasingly expected to provide informed oversight. Board-Ready AI Governance Templates equip directors and senior executives with practical, ready-to-use materials to govern AI responsibly and confidently.This book focuses on what boards actually need: clear papers, decision frameworks, and accountability structures that translate complex AI topics into governance-relevant information. I...

Generative AI is rapidly entering clinical and administrative workflows, introducing new risks to patient safety, data privacy, and regulatory compliance. Securing Generative AI in Healthcare provides a practical governance and security guide for healthcare organizations adopting AI responsibly.This book addresses the unique risk profile of healthcare AI, where errors, bias, or data leakage can directly affect patient outcomes. It explains how generative models differ from traditio...

As organizations increasingly adopt AI, employees need structured guidance to use these tools safely and responsibly. Building Internal AI Certifications provides a practical framework to design, implement, and manage internal training and micro-credential programs.Written for HR professionals, L&D teams, and organizational leaders, this book explains how to define learning objectives, assess competency, and recognize achievement with badges or certifications. It emphasizes respons...

Generative AI systems introduce new attack surfaces that traditional security testing does not cover. Red teaming is essential to uncover how large language models fail under adversarial conditions.Red Teaming Generative AI is a hands-on guide for security testers and engineers tasked with identifying weaknesses in LLM-based systems. The book focuses on practical testing techniques rather than theory, providing repeatable exercises that mirror real-world attack scenarios.It...

Small businesses increasingly face pressure to adopt AI to stay competitive, yet resources and expertise are often limited. AI for Small Businesses provides practical guidance on safely integrating AI into operations while capturing economic value.This book helps owners and managers understand where AI can add measurable benefit, how to evaluate tools, and implement simple but effective safeguards. It emphasizes low-complexity controls that protect data, maintain trust, and reduce ...

Synthetic data is increasingly used to accelerate AI development, protect sensitive information, and overcome data scarcity. However, poorly governed synthetic data can introduce hidden bias, privacy leakage, and regulatory risk that undermine its intended benefits.Governance for Synthetic Data is a technical yet practical guide for security, data, and AI leaders responsible for approving, deploying, and overseeing synthetic data initiatives. The book explains when synthetic data i...

As organizations increasingly procure AI-enabled products and services, contractual gaps have become a primary source of legal, operational, and financial risk. Standard technology agreements often fail to address the unique characteristics of AI systems, leaving buyers exposed.Contractual Controls for AI is a practical guide for procurement professionals, legal teams, and risk leaders responsible for negotiating and managing AI-related contracts. The book focuses on how to transla...

Machine learning systems are now business-critical infrastructure, yet many organizations deploy models without the operational security discipline applied to traditional software. Secure MLOps Fundamentals provides a practical, end-to-end security framework for building, deploying, and operating machine learning systems safely at scale.This book translates security principles into concrete MLOps controls that engineering and platform teams can apply immediately, without academic t...

Raising Kids in the Age of AI is a practical, authoritative guide for parents navigating a world where artificial intelligence is becoming part of everyday learning, communication, and creativity. As tools like ChatGPT enter classrooms and homes, parents face new questions about ethics, safety, misinformation, and academic integrity.This book helps parents understand how AI works at a high level—without technical jargon—and how it affects children's learning, thinking, and behavior...

Mental Health & The Digital World for Teens is a supportive, evidence-informed guide for parents navigating the emotional and psychological challenges adolescents face in a hyperconnected world. Social media, constant comparison, and online validation have reshaped how teens experience identity, confidence, and belonging.This book helps parents understand the connection between digital environments and teen anxiety, stress, and emotional fatigue—without alarmism or blame. It focuse...