Advanced in AI Risk (AAIR) Certification Training

• Domain 1: AI Risk Governance and Framework Integration 37%
  • AI Models, Frameworks, Strategies, and Use Cases
  • AI Organizational Processes and Alignment
  • AI Ownership, Oversight, and Accountability
  • AI Policies, Procedures, and Organizational Training
  • AI Regulatory Compliance and Legal Considerations
  • AI Trustworthiness, Ethical and Societal Implications (e.g., ESG)
• Domain 2: AI Life Cycle Risk Management 21%
  • AI Design, Development/Procurement, and Documentation
  • AI Model Training, Testing, and Validation
  • AI Implementation, Maintenance, and Decommissioning
  • AI Data and Asset Management
• Domain 3: AI Risk Program Management 42%
  • AI Risk Scenario Identification and Assessment (e.g., threats, vulnerabilities, and attacks)
  • AI Risk Treatment Strategies
  • Controls Management (e.g., Evaluation, Selection, Validation)
  • Risk Metrics, Monitoring, and Reporting
  • Supply Chain Risk Management (e.g., third party resources)
  • Incident Response, BIA, Business Continuity, and Disaster Recovery
• Other Skills Tested
  • Evaluate risk related to AI models/solutions including design, suitability, algorithms, training, drift, and AI life cycle.
  • Facilitate the integration of AI risk management into an enterprise risk management framework and risk programs.
  • Develop and implement an AI risk management framework, including roles and accountability, AI risk policies and procedures, and acceptable risk tolerance levels.
  • Conduct risk assessments to identify and classify risks associated with AI.
  • Develop and recommend risk treatment strategies for identified AI risks.
  • Assess compliance with applicable AI-related regulations, laws, frameworks, standards, and guidelines.
  • Integrate AI risk considerations into existing governance programs.
  • Evaluate AI use cases based on the organization’s risk appetite
  • Monitor and test organizational processes to identify AI risks.
  • Collaborate with stakeholders to develop and integrate AI risk concepts into enterprise-wide awareness training.
  • Capture AI risk considerations in enterprise risk metrics and reporting (e.g., board, management, operations).
  • Conduct and/or evaluate threat and vulnerability assessments on AI projects/programs.
  • Collaborate with stakeholders to integrate AI risk scenarios into the enterprise incident management program.
  • Continuously assess and monitor the risk landscape for emerging AI risk.
  • Evaluate controls to manage AI-related risk within the organization’s risk tolerance.
  • Advise on AI-related risk within contracts and service agreements, including data usage and intellectual property.
  • Evaluate AI risk as part of supply chain risk management.
  • Collaborate with stakeholders to address AI trustworthiness and impacts including ethics, bias, privacy, safety, and environmental, social, and governance (ESG) implications.
  • Leverage AI to support the risk management program (e.g., risk profile, reporting, evaluation, risk models, and analysis).
  • Integrate AI-related risk considerations into the change management process.
  • Incorporate AI-related risk considerations into incident response, BIAs, the BCP, and DRP.
  • Assess human oversight controls at critical decision points for risk and AI impact.

The training is ideal for:

• Risk Management Professionals
• IT Auditors and Internal Auditors
• Information Security and Cybersecurity Professionals
• Governance, Risk, and Compliance (GRC) Practitioners
• AI Governance and Responsible AI Leaders
• Technology and Digital Transformation Managers
• Data Governance and Privacy Professionals
• Enterprise Risk Managers
• CRISC, CISA, CISM, CISSP, and CGEIT Certified Professionals
• Executives and Decision-Makers overseeing AI adoption

• Active holders of industry-recognized certifications such as CISA, CISM, CRISC, CGEIT, CDPSE, and other relevant credentials seeking to expand their expertise in AI risk management.
• Experienced professionals working in IT risk, governance, compliance, audit, cybersecurity, consulting, or advisory roles who are responsible for assessing, managing, and mitigating technology-related risks.

• Understand the principles of AI risk management and the role of governance in ensuring responsible and secure AI adoption across the enterprise.
• Integrate AI risk management practices into existing enterprise governance, risk, compliance, and cybersecurity frameworks.
• Develop and implement AI governance structures, policies, controls, and oversight mechanisms aligned with organizational objectives and regulatory requirements.
• Apply AI lifecycle risk management techniques to identify and mitigate risks throughout the design, development, deployment, monitoring, and retirement phases of AI systems.
• Assess ethical, legal, regulatory, privacy, security, and operational risks associated with AI technologies and machine learning models.
• Design and manage enterprise-wide AI risk programs that support transparency, accountability, trustworthiness, and responsible AI practices.
• Establish effective AI risk monitoring, reporting, and continuous improvement processes to maintain compliance and organizational resilience.
• Evaluate emerging AI threats, regulatory developments, and industry best practices to strengthen AI governance and risk management strategies.
• Prepare for the ISACA AAIR certification exam by gaining a comprehensive understanding of the three core domains: AI Risk Governance and Framework Integration, AI Lifecycle Risk Management, and AI Risk Program Management.