The ISACA® Advanced in AI Security Management™ (AAIR™) certification validates risk professionals’ expertise and experience in managing AI-specific risks while harnessing AI’s transformative potential for strategic advantage. This credential builds upon established risk management best practices, focusing on the evolving AI landscape to effectively assess and manage risk profiles within organizations. By fostering cross-functional collaboration, it equips professionals to communicate AI risk comprehensively and ensure ethical and regulatory compliance. paragraph here
Course Details :
Two days
Approximately 12 hours Exam Duration
90 Questions. Must be completed in two hours
Required Prerequisites Must possess one of the following risk certifications: • CISA, CISM, CGEIT, CRISC, CDPSE, ACA, ACCA, ANAN CNA, CA ANZ, Canadian CPA, CERP, CGMA, CGRC, CIA, CISSP, CPA HKICPA, CRCM, CRMA, CRMP, CRMP-FED, FCA, FCA ANZ, FCCA, FCPA HKICPA, Japanese CPA, PMI-RMP, U.S. CPA CPE
Overview : A minimum of 10 hours of CPE/year in the AI domain
CPE can be applied to other certifications as part of the 20 annual/120 three-year requirement
No additional three-year requirement
Course Topics
1: AI Risk Governance and Framework Integration AI Models, Frameworks, Strategies, and Use Cases
Types of AI- AI Frameworks
Business Use Case and AI Use Case Review
AI Business Strategies AI Organizational Processes and Alignment
AI Governance Fundamentals
Alignment to Existing Organizational Structures AI Ownership, Oversight, and Accountability
AI-related Roles and Responsibilities
Accountability and AI
RACI for AI Solutions AI Policies, Procedures, and Organizational Training
AI Acceptable Use Policy
AI Policy Development
AI Procedures and Manuals
Organizational Culture and AI Risk Governance
Elements of Effective AI Training and Awareness
AI Regulatory Compliance and Legal Considerations
Compliance With Laws and Regulations
Gaps in Regulatory Coverage
Mapping Legal Requirements for AI
Assessing Legal Exposure and Liability for AI Actions
Intellectual Property Considerations in AI
Vendor Contract Review
AI Trustworthiness, Ethical and Societal Implications
Responsible Use of AI Systems 68
Bias and Fairness Transparency and Explainability
Trust and Safety
Human Rights and Societal Impact
2: AI Life Cycle Risk Management AI Design, Development, Procurement, and Documentation
Plan and Design
Data Requirements for AI Models
Procurement of AI Solutions
Build, Adapt, and Document Models
3: AI Risk Program Management AI Risk Scenario Identification and Assessment
AI Threat Landscape
AI Threat Modeling
Development of AI Risk Scenarios
AI Risk Classification
AI Risk Assessment
For more information
Christopher Nelson MBA, CISSP, PMP, ITIL, Expert, CSPO
Executive Director
Pinnacle Learning Centres Inc.
Phone: (647) 930 2379
16655 178 St NW #224, Edmonton, AB T5T 4J5
csanelson@pinnaclelearningcentres.com
www.pinnaclelearningcentres.com