AI Strategy and Security is a guide for organizations planning enterprise AI programs. The book targets technology leaders, security professionals, and executives responsible for strategy, governance, and operational execution. It treats AI adoption as an organizational discipline that spans planning, staffing, security engineering, risk management, and ongoing operations.
About the author
Dr. Donnie W. Wendt is a Lecturer at Columbus State University and a distinguished AI and cybersecurity professional. He is the author of The Cybersecurity Trinity: Artificial Intelligence, Automation, and Active Cyber Defense and co-author of the AI Adoption & Management Framework.
Inside the book
The book opens with strategy development and places AI within standard business planning processes. Wendt frames AI initiatives around business objectives such as differentiation, market expansion, process optimization, and workforce enablement. Each objective is described through practical examples drawn from sectors like finance, healthcare, retail, manufacturing, and energy. The emphasis stays on alignment with organizational goals, measurable outcomes, and leadership involvement.
Preparation for adoption receives significant attention in the early chapters. Wendt outlines readiness assessments across technical capabilities, data maturity, personnel skills, and organizational culture. Infrastructure planning includes computing resources, storage systems, networking requirements, and deployment models. Cloud, on premises, and hybrid approaches are described with attention to compliance, scalability, and cost management.
Team composition forms a separate focus area. The book defines roles across AI engineering, data science, MLOps, security, governance, and ethics. Titles such as Chief AI Officer, AI architect, AI security engineer, and AI ethics officer are described in terms of responsibilities and collaboration patterns. Wendt presents these roles as part of an integrated delivery model that connects strategy, development, security testing, and operations. Workforce development, training pipelines, and continuous learning are treated as ongoing requirements rather than one time efforts.
Security occupies a central position in the book’s structure. Dedicated chapters address AI specific attack vectors, including data poisoning, model manipulation, backdoor insertion, privacy attacks, and supply chain risks tied to shared datasets and pre trained models. Wendt connects these risks to concrete defensive practices such as data handling controls, model change management, API protection, adversarial testing, monitoring, and drift analysis.
The book outlines governance structures, accountability models, policy development, and risk assessment workflows tailored to AI systems. Inventory management, third party risk oversight, and continuous monitoring appear as core governance functions. Regulatory considerations include U.S. and international frameworks, privacy obligations, and emerging AI specific standards.
Responsible AI receives its own section with attention to societal, organizational, and individual impacts. Topics include transparency, explainability, accountability, bias mitigation, and ethical design practices. The discussion links ethical considerations to operational processes such as impact assessments, human oversight, and documentation. This section treats responsibility as a management practice that integrates with governance and security activities.
Later chapters focus on operationalization and continuous improvement. Deployment processes, monitoring practices, lifecycle management, and performance evaluation are addressed with an emphasis on repeatability and measurement. Wendt describes AI operations as a living system that evolves through feedback loops, retraining, and decommissioning when systems reach the end of their useful life. Cultural change, communication, and education appear as supporting elements that influence long-term adoption.
Conclusion
AI Strategy and Security works best for CISOs, security architects, risk leaders, and technology executives who need a single reference that connects AI strategy with security, governance, and operations in a coherent way.