Build the expertise to govern AI responsibly through effective oversight, ethics, risk management, and compliance.
The Certified Responsible AI Governance & Ethics Professional (C|RAGE) credential prepares professionals to manage AI governance throughout the AI lifecycle, from policy and oversight to controls, compliance, testing, validation, and assurance. It focuses on making AI systems trustworthy, defensible, secure, and compliant at scale.
- Why get trained: Learn to establish AI governance structures, define roles and accountability, apply ethical principles, manage regulatory obligations, assess AI risks, conduct AI testing and audits, and oversee third party AI risks.
- Why it matters: Effective AI governance helps organizations strengthen accountability, support regulatory compliance, reduce AI related risks, build stakeholder trust, and enable responsible innovation.
- Who should attend: Audit Professionals, GRC and Risk Management Professionals, Compliance and Regulatory Professionals, Privacy Professionals, Data Governance Professionals, and others responsible for AI governance and oversight.
Build the skills to establish responsible AI governance and support ethical, secure, compliant, and accountable AI adoption across your organization. HRD Corp Claimable.
Overview
Nearly 80% of organizations deploy AI without a defined governance owner or operating model. Regulations are tightening. Enterprises need leaders who can embed governance throughout the AI life cycle, from ideation to deployment.
EC-Council’s Certified Responsible AI Governance & Ethics Professional (C|RAGE) credential validates your ability to operationalize governance aligned with NIST AI RMF and ISO/IEC 42001, helping enterprises scale AI with accountability.
C|RAGE is a professional certification built to prepare professionals to govern AI systems responsibly across their life cycle: from
policy and oversight to controls, compliance, and assurance. C|RAGE equips you to:
- Establish governance structures, roles, and decision authority
- Apply ethical principles in operational, enforceable ways
- Manage regulatory obligations and audit readiness
- Assess AI risks and enforce accountability across design, deployment, and operation
Certified Responsible AI Governance & Ethics Professional (C|RAGE) is not a model-building certification. It is for professionals responsible for making AI trustworthy, defensible, and compliant at scale.
Skills Covered
- Become a recognized leader who ensures AI systems are trusted, fair, and compliant. Guide organizations to avoid bias, legal risk, and reputational damage.
- Build governance and audit-ready AI programs that meet global regulatory standards (EU AI Act, NIST RMF, ISO/IEC 23894, etc.), so AI deployments can scale internationally with confidence.
- Establish ethical culture and transparent practices in AI development so that data teams, product teams and leadership operate with accountability, reducing risks and increasing stakeholder trust.
Prerequisites
Participants are required to have at least 3 years of cybersecurity experience
Target Audience
CRAGE is designed for professionals who must ensure AI is ethical, compliant, secure, and accountable, regardless of whether they build models.
- Audit
- GRC and Risk Management
- Compliance and Regulatory
- Privacy and Data Governance
Module 1: AI Foundations and Technology Ecosystem
- Understand core principles, evolution, and components of AI
- Apply real-world AI applications across industries
- Apply AI project life cycle, MLOps, and DataOps
- Apply AI technology stack, infrastructure, and deployment models
Module 2: AI Concerns, Ethical Principles, and Responsible AI
- Understand key ethical, societal, privacy, and security concerns in AI
- Understand fundamental AI ethics principles and global standards
- Apply Responsible AI usage practices for safe and accountable AI
- Apply Responsible AI development life cycle and governance integration
Module 3: AI Strategy and Planning
- Set an AI vision and assess organizational readiness
- Prioritize use-case and develop an AI roadmap
- Modernize data, technology, and infrastructure
- Manage AI pilots, scaling strategies, culture, and performance
Module 4: AI Governance and Frameworks
- Understand AI governance concepts, operating models, and roles
- Define AI governance policies, decision rights, and controls
- Apply global AI governance frameworks and life cycle governance
- Manage AI asset management, documentation, human oversight, and tooling
Module 5: AI Regulatory Compliance
- Understand global and sector-specific AI regulatory requirements
- Understand accountability, liability, and user rights in AI systems
- Apply operational compliance, reporting, and audit readiness
- Implement continuous compliance monitoring and legal risk management
Module 6: AI Risk and Threat Management
- Understand AI threat landscape, vulnerabilities, and adversarial attacks
- Apply AI risk identification, assessment, and prioritization methods
- Apply AI risk management frameworks and standards
- Conduct threat modeling and attack surface analysis for AI systems
Module 7: Third-Party AI Risk Management and Supply Chain Security
- Understand third-party AI risk categories and supply chain threats
- Conduct AI vendor due diligence, evaluation, and contract governance
- Apply regulatory obligations and vendor compliance requirements
- Implement continuous vendor monitoring, assurance, and incident response
Module 8: AI Security Architecture and Controls
- Understand AI security architecture principles and frameworks
- Apply secure AI design patterns and defense-in-depth strategies
- Implement secure coding, model protection, and deployment controls
- Apply runtime security, API protection, and continuous monitoring
Module 9: Building Privacy, Trust, and Safety in AI Systems.
- Understand privacy-enhancing technologies and data protection techniques
- Apply AI privacy risk assessment and mitigation strategies
- Apply transparency, explainability, and trust building mechanisms
- Implement ethical design, fairness assurance, and trust monitoring
Module 10: AI Incident Response and Business Continuity
- Understand AI-focused incident response frameworks and workflows
- Conduct AI incident detection, containment, recovery, and reporting
- Develop AI business continuity and disaster recovery planning
- Apply testing, simulations, and continuous readiness improvement
Module 11: AI Assurance, Testing, and Auditing
- Understand AI assurance principles, frameworks, and governance models
- Apply AI testing strategies across data, models, and systems
- Conduct validation, verification, bias, fairness, and robustness testing
- Apply AI auditing methodologies, evidence management, and reporting
Dates & Locations
January 19, 2027 - January 21, 2027
January 19, 2027 - January 21, 2027
April 20, 2027 - April 22, 2027
April 20, 2027 - April 22, 2027
July 13, 2027 - July 15, 2027
July 13, 2027 - July 15, 2027
October 25, 2027 - October 27, 2027
October 25, 2027 - October 27, 2027
Exam & Certification
Certified Responsible AI Governance & Ethics Professional.
The Certified Responsible AI Governance & Ethics Professional (C|RAGE) credential prepares professionals to govern AI systems throughout their lifecycle, from strategy, policy, and oversight to risk management, compliance, testing, validation, and assurance. It focuses on establishing trustworthy, defensible, secure, and compliant AI governance practices at scale.
C|RAGE covers AI foundations, responsible AI and ethical principles, AI governance frameworks, regulatory compliance, AI risk and threat management, third-party AI risk, security architecture and controls, privacy, trust and safety, incident response, business continuity, and AI assurance, testing, and auditing. The program helps professionals develop the expertise required to support accountable and responsible AI adoption across organizations.
Training & Certification Guide
Frequently Asked Questions
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