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The CISO's Guide to AI Governance. The CyberInsider Executive Series, #1
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- FormatePub
- ISBN8232075941
- EAN9798232075941
- Date de parution29/11/2025
- Protection num.pas de protection
- Infos supplémentairesepub
- ÉditeurDraft2Digital
Résumé
Bridging the gap between technical cybersecurity and executive strategy. As Artificial Intelligence moves from research labs to the heart of enterprise decision-making, the role of the Chief Information Security Officer (CISO) is evolving. It is no longer enough to secure networks; CISOs must now govern the integrity, fairness, and safety of the algorithmic systems driving the business. The CISO's Guide to AI Governance provides a practical roadmap for security leaders, board members, and compliance officers tasked with overseeing AI adoption.
Drawing on emerging global standards and real-world risk frameworks, this guide translates complex AI concepts into actionable governance strategies. What You Will Learn: The AI Risk Landscape: Mitigate novel threats like prompt injection, data poisoning, and model inversion. Regulatory Readiness: A step-by-step approach to complying with the EU AI Act, NIST AI RMF, and ISO 42001. Secure MLOps: Embed security by design into your pipelines and establish a rigorous AI Review Board.
Supply Chain Resilience: Master third-party risk management and vet AI vendors to prevent downstream attacks. Measuring Success: Define KPIs and reporting frameworks to demonstrate the ROI of safe AI adoption to the Board. Whether you are battling "Shadow AI, " implementing Generative AI tools, or building proprietary models, this handbook equips you with the vocabulary and frameworks needed to lead the conversation on Responsible AI.
Drawing on emerging global standards and real-world risk frameworks, this guide translates complex AI concepts into actionable governance strategies. What You Will Learn: The AI Risk Landscape: Mitigate novel threats like prompt injection, data poisoning, and model inversion. Regulatory Readiness: A step-by-step approach to complying with the EU AI Act, NIST AI RMF, and ISO 42001. Secure MLOps: Embed security by design into your pipelines and establish a rigorous AI Review Board.
Supply Chain Resilience: Master third-party risk management and vet AI vendors to prevent downstream attacks. Measuring Success: Define KPIs and reporting frameworks to demonstrate the ROI of safe AI adoption to the Board. Whether you are battling "Shadow AI, " implementing Generative AI tools, or building proprietary models, this handbook equips you with the vocabulary and frameworks needed to lead the conversation on Responsible AI.
Bridging the gap between technical cybersecurity and executive strategy. As Artificial Intelligence moves from research labs to the heart of enterprise decision-making, the role of the Chief Information Security Officer (CISO) is evolving. It is no longer enough to secure networks; CISOs must now govern the integrity, fairness, and safety of the algorithmic systems driving the business. The CISO's Guide to AI Governance provides a practical roadmap for security leaders, board members, and compliance officers tasked with overseeing AI adoption.
Drawing on emerging global standards and real-world risk frameworks, this guide translates complex AI concepts into actionable governance strategies. What You Will Learn: The AI Risk Landscape: Mitigate novel threats like prompt injection, data poisoning, and model inversion. Regulatory Readiness: A step-by-step approach to complying with the EU AI Act, NIST AI RMF, and ISO 42001. Secure MLOps: Embed security by design into your pipelines and establish a rigorous AI Review Board.
Supply Chain Resilience: Master third-party risk management and vet AI vendors to prevent downstream attacks. Measuring Success: Define KPIs and reporting frameworks to demonstrate the ROI of safe AI adoption to the Board. Whether you are battling "Shadow AI, " implementing Generative AI tools, or building proprietary models, this handbook equips you with the vocabulary and frameworks needed to lead the conversation on Responsible AI.
Drawing on emerging global standards and real-world risk frameworks, this guide translates complex AI concepts into actionable governance strategies. What You Will Learn: The AI Risk Landscape: Mitigate novel threats like prompt injection, data poisoning, and model inversion. Regulatory Readiness: A step-by-step approach to complying with the EU AI Act, NIST AI RMF, and ISO 42001. Secure MLOps: Embed security by design into your pipelines and establish a rigorous AI Review Board.
Supply Chain Resilience: Master third-party risk management and vet AI vendors to prevent downstream attacks. Measuring Success: Define KPIs and reporting frameworks to demonstrate the ROI of safe AI adoption to the Board. Whether you are battling "Shadow AI, " implementing Generative AI tools, or building proprietary models, this handbook equips you with the vocabulary and frameworks needed to lead the conversation on Responsible AI.
