Certified AI & Quantum Risk Assessment Specialist (CAQRAS)

Certified AI & Quantum Risk Assessment Specialist CAQRAS Certification Program by Tonex equips professionals to identify, assess, quantify, and manage emerging risks created by AI systems and quantum-era threats. Participants learn how to build realistic threat scenarios, translate technical exposures into business impact, and maintain defensible risk registers for AI and quantum-enabled environments. The program connects model risk management with assurance practices, audit readiness, and executive governance, helping teams operationalize controls without slowing innovation.

A strong emphasis is placed on cybersecurity implications including adversarial ML, data integrity, model misuse, and cryptographic disruption from quantum advances. You will practice communicating risk appetite, control effectiveness, and residual risk in terms leaders can act on, while aligning methods to recognized frameworks and standards. By the end, graduates can support enterprise decision-making with evidence-based assessments, compliance mapping, and board-level reporting that strengthens cybersecurity posture across products, platforms, and operations.

Learning Objectives

• Build AI risk models that map assets, threats, controls, and residual risk
• Perform quantum risk impact analysis for cryptography and critical workflows
• Design and maintain risk registers for AI and quantum systems
• Apply model risk management practices across lifecycle governance and change control
• Prepare assurance evidence for audit readiness and third-party scrutiny
• Communicate measurable cybersecurity impact to executives using defensible metrics
• Map regulatory and standards requirements into implementable risk controls

Audience

• Risk managers and enterprise risk teams
• Compliance leaders and audit stakeholders
• CISOs and security governance teams
• Model risk and AI governance owners
• Cybersecurity Professionals
• Business continuity and resilience leaders

Program Modules

Module 1: AI Risk Modeling Foundations

• AI asset and data inventory methods
• Threat scenario design and prioritization
• Attack surface mapping for AI pipelines
• Control selection and risk treatment options
• Residual risk scoring and calibration
• Documentation standards for governance

Module 2: Quantum Risk Impact Analysis

• Quantum threat overview for security planning
• Crypto dependency discovery and classification
• Exposure analysis for vulnerable algorithms
• Migration risk and timeline estimation
• Compensating controls and interim safeguards
• Reporting quantum readiness to leadership

Module 3: Risk Registers For Emerging Systems

• Register structure and taxonomy design
• Risk statements and evidence traceability
• Likelihood and impact scoring techniques
• Ownership, actions, and due date governance
• KRIs and thresholds for monitoring
• Continuous updates and exception handling

Module 4: Model Risk Management Practices

• Model lifecycle governance and approval gates
• Validation planning and independence principles
• Data drift, concept drift, and triggers
• Performance, bias, and robustness testing criteria
• Change management and version accountability
• Remediation tracking and sign-off workflows

Module 5: AI Assurance And Audit Readiness

• Assurance objectives and control mapping
• Evidence collection and defensible artifacts
• Audit narratives and risk control linkage
• Third-party model and vendor assessment
• Incident learnings into assurance updates
• Executive-ready assurance reporting packs

Module 6: Governance Reporting And Compliance Mapping

• Regulatory obligation identification methods
• NIST AI RMF alignment for risk governance
• ISO 27001 control mapping for cybersecurity
• ISO 42001 governance alignment for AI systems
• ISO 23894 risk management alignment for AI
• Board-level reporting structure and storytelling

Exam Domains

1. Quantitative Risk Metrics and Scoring Methods
2. Governance Operating Models and Risk Appetite
3. Control Effectiveness Measurement and Assurance
4. Third-Party and Supply Chain Risk Oversight
5. Business Continuity and Resilience Integration
6. Executive Reporting, Escalation, and Decision Support

Course Delivery
The course is delivered through a combination of lectures, interactive discussions, hands-on workshops, and project-based learning, facilitated by experts in the field of Certified AI & Quantum Risk Assessment Specialist CAQRAS. Participants will have access to online resources, including readings, case studies, and tools for practical exercises.

Assessment and Certification
Participants will be assessed through quizzes, assignments, and a capstone project. Upon successful completion of the course, participants will receive a certificate in Certified AI & Quantum Risk Assessment Specialist CAQRAS.

Question Types

• Multiple Choice Questions (MCQs)
• Scenario-based Questions

Passing Criteria
To pass the Certified AI & Quantum Risk Assessment Specialist CAQRAS Certification Training exam, candidates must achieve a score of 70% or higher.

Enroll in the CAQRAS Certification Program by Tonex to strengthen enterprise-ready AI and quantum risk governance and deliver clear, executive-grade decisions that improve cybersecurity outcomes across your organization.