AI Strategy and Security (eBook, PDF)
A Roadmap for Secure, Responsible, and Resilient AI Adoption
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AI will fundamentally change the way business is conducted across most industries. Organizations that excel at leveraging secure, responsible AI to advance their strategic objectives will have a distinct advantage. Those that do not may see their market share erode.This book provides a guide for organizations to integrate AI in alignment with the organization's strategic goals. The framework provides a roadmap for adopting secure, responsible, and resilient AI, from initial strategy development to ongoing operations that will help advance market leadership.Part one of the book discusses laying...
AI will fundamentally change the way business is conducted across most industries. Organizations that excel at leveraging secure, responsible AI to advance their strategic objectives will have a distinct advantage. Those that do not may see their market share erode.
This book provides a guide for organizations to integrate AI in alignment with the organization's strategic goals. The framework provides a roadmap for adopting secure, responsible, and resilient AI, from initial strategy development to ongoing operations that will help advance market leadership.
Part one of the book discusses laying a solid foundation to ensure successful AI integration, beginning with developing an AI strategy aligned with strategic business objectives, such as product and service differentiation, market expansion, and process optimization.
Part Two takes a deep dive into ensuring secure and safe AI adoption. It proposes a secure-by-design approach to AI development that considers AI-specific attack vectors and associated security practices throughout the AI lifecycle.
Developing and deploying secure, responsible, and resilient AI is not a one-time effort. Therefore, Part Three discusses operationalizing AI and integrating it throughout the enterprise to ensure continued success. This section focuses on scaling AI applications and continuous improvement, including establishing metrics and conducting a post-deployment ROI evaluation. Finally, it discusses how to foster a culture of AI innovation and excellence, ensuring that AI becomes a way of doing business.
What You Will Learn:
Who This Book is for:
The primary audience includes business leaders, AI practitioners, AI executives, AI governance professionals, and cybersecurity leaders looking to integrate AI as a strategic differentiator and to enhance business operations. Higher education would be a secondary audience.
This book provides a guide for organizations to integrate AI in alignment with the organization's strategic goals. The framework provides a roadmap for adopting secure, responsible, and resilient AI, from initial strategy development to ongoing operations that will help advance market leadership.
Part one of the book discusses laying a solid foundation to ensure successful AI integration, beginning with developing an AI strategy aligned with strategic business objectives, such as product and service differentiation, market expansion, and process optimization.
Part Two takes a deep dive into ensuring secure and safe AI adoption. It proposes a secure-by-design approach to AI development that considers AI-specific attack vectors and associated security practices throughout the AI lifecycle.
Developing and deploying secure, responsible, and resilient AI is not a one-time effort. Therefore, Part Three discusses operationalizing AI and integrating it throughout the enterprise to ensure continued success. This section focuses on scaling AI applications and continuous improvement, including establishing metrics and conducting a post-deployment ROI evaluation. Finally, it discusses how to foster a culture of AI innovation and excellence, ensuring that AI becomes a way of doing business.
What You Will Learn:
- Develop an AI integration strategy aligned with the organization's strategic goals and objectives.
- Incorporate a secure-by-design approach to AI integration that considers AI-specific attack vectors and applies traditional and AI-specific defense methods, such as adversarial development, model behavior monitoring, drift analysis, input validation and filtering, and output filtering.
- Establish an AI governance and risk management framework to ensure ongoing compliance with applicable legislation, industry standards, organizational policies, and responsible AI principles.
- Operationalize and scale AI applications to ensure resilient production usage and facilitate continuous improvement.
- Foster a culture of AI innovation and excellence, ensuring that AI becomes a way of doing business.
Who This Book is for:
The primary audience includes business leaders, AI practitioners, AI executives, AI governance professionals, and cybersecurity leaders looking to integrate AI as a strategic differentiator and to enhance business operations. Higher education would be a secondary audience.
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