Global AI governance market to reach $3.590B by 2033 (Grand View Research)

Certified Responsible
AI Governance & Ethics

Be EN-RAGED by the Chaos. Lead the Mandate for Responsible AI Governance.

Enterprises need leaders who can embed governance throughout the AI lifecycle, from ideation to deployment. This credential validates your ability to operationalize governance aligned with NIST AI RMF and ISO/IEC 42001, helping enterprises scale AI with accountability.

11 Comprehensive Modules

Framework-Driven, Regulation-Aligned Curriculum

Scenario-Based Governance and Risk Analysis

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The AI Governance Crisis

Enterprises Need
Certified AI
Governance Professionals

AI is moving from experimentation to infrastructure. Enterprises need leaders who can embed governance throughout the AI lifecycle, from ideation to deployment, so they can scale AI with accountability and meet regulatory requirements.

When AI fails, leadership is accountable.
C|RAGE certifies professionals who can stand behind AI decisions.

The Governance Gap Organizations Face
  • Companies deploy AI, but lack governance frameworks to manage risk
  • Legal teams understand compliance, but can't translate AI technical risks
  • Data scientists build models, but don't own ethics accountability
  • Result: AI deployments without governance = regulatory exposure

Problem

95% of AI initiatives fail to reach production. Organizations invest millions in AI tools but lack professionals who can bridge the gap between technical execution and business impact.

Solution

C|AIPM certification equips you to lead AI projects end-to-end—from ideation to deployment. Master governance frameworks, MLOps, and stakeholder management.

THE PROBLEM

AI governance gaps expose organizations to regulatory, reputational, and operational risks. Without certified governance professionals, enterprises deploy AI without accountability.

  • No verified AI governance skills in the market
  • Organizations deploy AI without accountability
  • Audit failures waiting to happen

C|RAGE Credential Validates

The C|RAGE certification equips you to lead AI governance end-to-end, from policy design to audit readiness. Master compliance frameworks, risk management, and ethical oversight.

  • Validate your ability to embed governance across the AI lifecycle
  • Verify skills in building audit-ready programs from ideation to deployment
  • Prove you can help enterprises scale AI with accountability
Master AI governance and compliance frameworks

Lead enterprise-wide AI accountability initiatives

Ensure regulatory readiness with audit-ready programs

The AI Governance Crisis

Organizations
Can't Govern
AI Responsibly

AI regulation is accelerating globally, but most organizations lack the governance expertise needed to stay compliant.

Enterprises need certified AI Governance professionals who can build ethical frameworks, ensure regulatory compliance, and manage AI risk across the organization.

Gartner predicts 75% of organizations will face AI compliance audits by 2027.1 McKinsey reports only 18% have formal AI governance in place.2

1 Gartner AI Governance Report, 2025   2 McKinsey AI Survey, 2025

The Governance Gap Organizations Face
  • Companies deploy AI, but lack governance frameworks to manage risk
  • Legal teams understand compliance, but can't translate AI technical risks
  • Data scientists build models, but don't own ethics accountability
  • Result: AI deployments without governance = regulatory exposure

Problem

95% of AI initiatives fail to reach production. Organizations invest millions in AI tools but lack professionals who can bridge the gap between technical execution and business impact.

Solution

C|AIPM certification equips you to lead AI projects end-to-end—from ideation to deployment. Master governance frameworks, MLOps, and stakeholder management.

What C|RAGE Validates

Verify the skills that make you the governance leader organizations need:

  • This credential validates your ability to lead AI governance programs
  • Verified skills in AI ethics, compliance, and risk management
  • Credential proves confidence advising executives on responsible AI
  • Industry-recognized proof of AI regulatory readiness
  • Validation that you can bridge the governance gap organizations need

What Your Organization Gets

Solve the AI governance crisis:

  • Establish AI governance before regulatory penalties arise
  • Build trust with customers through responsible AI practices
  • Align AI deployments with global compliance standards
  • Clear accountability frameworks for AI decision-making
Master AI governance and compliance frameworks

Lead enterprise-wide AI accountability initiatives

Ensure regulatory readiness with audit-ready programs

What Most Organizations Do:

"Let's deploy AI and figure out governance later"

Organizations with C|RAGE Certified professionals:

Govern AI with Ethics
and Responsible
practices

$5.5 TRILLION IN UNMANAGED AI RISK (IDC)🔥WORKFORCE READINESS IS THE PRIMARY CONSTRAINT (IMF & WEF)📉 THIS CREDENTIAL VALIDATES YOUR AI GOVERNANCE SKILLS🛡️ VERIFY NIST AI RMF & ISO 42001 COMPLIANCE EXPERTISE⚠️ $5.5 TRILLION IN UNMANAGED AI RISK (IDC)🔥 WORKFORCE READINESS IS THE PRIMARY CONSTRAINT (IMF & WEF)📉 THIS CREDENTIAL VALIDATES YOUR AI GOVERNANCE SKILLS🛡️ VERIFY NIST AI RMF & ISO 42001 COMPLIANCE EXPERTISE⚠️ 80% OF COMPANIES USE AI BUT LACK PROGRAM LEADERSHIP TO SCALE — MCKINSEY🔥 $5.5 TRILLION IN UNMANAGED AI RISK (IDC)📉 WORKFORCE READINESS IS THE PRIMARY CONSTRAINT (IMF & WEF)🛡️ THIS CREDENTIAL VALIDATES YOUR AI GOVERNANCE SKILLS

The AI Governance Skills Gap

ORGANIZATIONS
CAN'T GOVERN AI

Nearly 80% of organizations deploy AI without a defined governance owner or operating model*. Regulations are tightening. They need professionals with verified skills to build audit-ready programs.

This credential validates the governance skills organizations desperately need; professionals who can own AI accountability, compliance, and risk management.

*Source: McKinsey Global AI Survey

The Market Problem

Why AI Governance Fails

  • Organizations deploy AI without governance ownership
  • Compliance gaps with NIST AI RMF & ISO 42001 regulations
  • No verified skills for AI auditing and validation
  • Unclear accountability when AI systems fail
  • Regulatory penalties approaching as AI rules tighten

What This Credential Validates

C|RAGE HELPS:

  • Validate you can lead AI governance across teams
  • Verify your skills in building regulatory-compliant AI programs
  • Prove your ability to execute AI testing, validation, and auditing
  • Validate your expertise in AI risk assessment and third-party AI risk
  • Demonstrate you can define enterprise AI strategy and accountability
What This Credential Validates

Organizations need verified AI governance skills. This credential proves you have them.

If your role involves AI governance, GRC, compliance, or policy, this program helps you validate those skills.

That's you!

19+

Target Roles

IS C|RAGE RIGHT FOR YOU?

Who is C|RAGE Ideal For

This program is designed for professionals across security, IT, and business functions who want to lead AI initiatives.

GRC & Risk Management

Head of Governance, Risk & Compliance (GRC)
GRC Manager
Director, Risk Management
Risk Manager
Head of Enterprise Risk Management (ERM)
Operational Risk Manager

Compliance & Regulatory

Director, Compliance
Compliance Manager
Director, Regulatory Affairs
Regulatory Compliance Manager

Privacy & Data Governance

Chief Privacy Officer
Director of Privacy
Privacy Program Manager
Data Protection Officer (DPO)
Data Governance Manager
Director, Data Governance

Audit

Internal Audit Manager (Technology / IT)
Technology Audit Manager
Director, Internal Audit
Become the Solution

11 comprehensive modules

Program Overview

11 comprehensive modules!

Master AI governance, ethics, and compliance across the enterprise. The C|RAGE certification covers oversight, risk management, regulatory alignment, and accountability across the AI lifecycle.

Module 01

AI Foundations and Technology Ecosystem

Master the foundational concepts, technologies, and operational lifecycle of artificial intelligence to understand how modern AI systems are built, deployed, and scaled responsibly.

What You'll Learn

Core principles, evolution, and components of AI
Real-world AI applications across industries
AI project lifecycle, MLOps, and DataOps
AI technology stack, infrastructure, and deployment models
Duration: 60 min
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Module 02

AI Concerns, Ethical Principles, and Responsible AI

Master ethical AI principles and frameworks to ensure responsible AI development and deployment across your organization.

What You'll Learn

Key ethical, societal, privacy, and security concerns in AI
Fundamental AI ethics principles and global standards
Responsible AI usage practices for safe and accountable AI
Responsible AI development lifecycle and governance integration
Duration: 45 min
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Module 03

AI Strategy and Planning

Develop structured AI strategies and roadmaps that align organizational goals with responsible, scalable, and value-driven AI adoption.

What You'll Learn

AI vision setting and organizational readiness assessment
Use-case prioritization and AI roadmap development
Data, technology, and infrastructure modernization
AI pilots, scaling strategies, culture, and performance management
Duration: 55 min
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Module 04

AI Governance and Frameworks

Design and implement enterprise-wide AI governance structures that ensure accountability, transparency, compliance, and trust.

What You'll Learn

AI governance concepts, operating models, and roles
AI governance policies, decision rights, and controls
Global AI governance frameworks and lifecycle governance
AI asset management, documentation, human oversight, and tooling
Duration: 50 min
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Module 05

AI Regulatory Compliance

Navigate global AI regulations and compliance obligations to ensure lawful, ethical, and defensible AI deployments.

What You'll Learn

Global and sector-specific AI regulatory requirements
Accountability, liability, and user rights in AI systems
Operational compliance, reporting, and audit readiness
Continuous compliance monitoring and legal risk management
Duration: 45 min
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Module 06

AI Risk and Threat Management

Identify, assess, and manage AI-specific risks, threats, and vulnerabilities across the AI lifecycle.

What You'll Learn

AI threat landscape, vulnerabilities, and adversarial attacks
AI risk identification, assessment, and prioritization methods
AI risk management frameworks and standards
Threat modeling and attack surface analysis for AI systems
Duration: 70 min
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Module 07

Third-Party AI Risk Management and Supply Chain Security

Manage vendor, supplier, and ecosystem risks across AI procurement, deployment, and lifecycle operations.

What You'll Learn

Third-party AI risk categories and supply chain threats
AI vendor due diligence, evaluation, and contract governance
Regulatory obligations and vendor compliance requirements
Continuous vendor monitoring, assurance, and incident response
Duration: 60 min
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Module 08

AI Security Architecture and Controls

Design secure-by-design AI architectures that protect models, data, pipelines, and runtime environments.

What You'll Learn

AI security architecture principles and frameworks
Secure AI design patterns and defense-in-depth strategies
Secure coding, model protection, and deployment controls
Runtime security, API protection, and continuous monitoring
Duration: 55 min
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Module 09

Building Privacy, Trust, and Safety in AI Systems

Embed privacy, transparency, trust, and safety into AI systems to enable ethical and user-centric AI experiences.

What You'll Learn

Privacy-enhancing technologies and data protection techniques
AI privacy risk assessment and mitigation strategies
Transparency, explainability, and trust-building mechanisms
Ethical design, fairness assurance, and trust monitoring
Duration: 50 min
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Module 10

AI Incident Response and Business Continuity

Build AI-specific incident response, resilience, and recovery capabilities to sustain trust and business operations.

What You'll Learn

AI-focused incident response frameworks and workflows
AI incident detection, containment, recovery, and reporting
AI business continuity and disaster recovery planning
Testing, simulations, and continuous readiness improvement
Duration: 55 min
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Module 11

AI Assurance, Testing, and Auditing

Establish robust assurance, testing, and audit mechanisms to validate trustworthy, compliant, and reliable AI systems.

What You'll Learn

AI assurance principles, frameworks, and governance models
AI testing strategies across data, models, and systems
Validation, verification, bias, fairness, and robustness testing
AI auditing methodologies, evidence management, and reporting
Duration: 55 min
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The ADG Framework

AI Governance & Ethics
Methodology

From risk assessment to policy implementation, compliance to continuous monitoring, there's a structured approach to governing AI responsibly.

This framework equips you to lead AI governance with confidence and accountability.

01 ASSESS

Identify AI risks, conduct gap analysis, and evaluate governance maturity to understand your organization's current state and compliance readiness.

02 GOVERN

Design policies, implement controls, and establish oversight mechanisms to ensure ethical AI use, regulatory compliance, and clear accountability.

03 SUSTAIN

Monitor AI systems continuously, report on governance metrics, and drive improvement to maintain trust and adapt to evolving regulations.

Inventory
Risk Eval
Compliance
Ethics
Policy
Accountability
Audit
Transparency
Bias
Evaluation
Stakeholders
Regulation
Risk ID
Gaps
Maturity
Policy
Controls
Oversight
Monitor
Report
Improve
ASSESS
GOVERN
SUSTAIN

C|RAGE

Framework

THE GOVERNANCE GAP

WHY AI
GOVERNANCE
REQUIRES NEW FRAMEWORKS

AI regulations are tightening globally. Organizations without proper governance frameworks face regulatory penalties, audit failures, and accountability gaps.

Nearly 80% of organizations deploy AI without a defined governance owner or operating model.

The problem isn’t technology. It’s the lack of verified governance leadership.

Insufficient

Organizations can't just:

  • Generic IT governance frameworks
  • Standard software security controls
  • Traditional compliance checklists
  • Basic risk management processes
The Gap

Reality Check

They must also address:

  • Model bias, drift, and hallucination accountability
  • Regulatory compliance with NIST AI RMF & EU AI Act
  • AI auditing, assurance, and validation requirements
  • AI lifecycle and portfolio management
  • Cross-functional AI oversight and accountability

THE SOLUTION

Master the World’s Most Critical AI Governance Frameworks

C|RAGE Certified

You'll master:

NIST AI RMF
•
ISO/IEC 42001
•
EU AI Act
•
GDPR/CCPA
•
SOC 2
•
Global AI Ethics Standards

This is what separates reactive compliance from proactive governance:
Become an AI Governance Authority - trusted to design, govern, audit, and sustain responsible AI at enterprise scale.

Compliance, Ethics, and Accountability AI at scale.

Enroll in C|RAGE

BUILD RESPONSIBLE AI GOVERNANCE FRAMEWORKS

GOVERN.
COMPLY.
LEAD.

One framework. Enterprise-wide AI trust.

The C|RAGE program equips you with comprehensive expertise across AI governance, risk management, and ethical oversight, from regulatory compliance to organizational accountability.

You'll learn to design, implement, and manage AI governance frameworks that ensure regulatory compliance, mitigate risks, and build stakeholder trust across the enterprise.

Ethics Framework

Bias Detection

Impact Analysis

Policy Design

Incident Response

Audit Readiness

AI Transparency Data Privacy

Risk Assessment

Compliance Audit

Explore the Full Curriculum

AI Program Management Frameworks

TOOLS &
TECHNIQUES
YOU WILL MASTER

Practical frameworks and methodologies used by leading AI program managers at Fortune 500 companies.

No roadmap for AI investment
AI Strategy Frameworks

Enterprise AI roadmapping, portfolio planning, and value prioritization

Wrong use cases get funded
Use Case Evaluation

ROI-driven assessment and prioritization of AI for business intelligence

Models fail in production
MLOps Principles

Model lifecycle management for scalable, production-ready AI

Compliance gaps create risk
AI Governance

Risk, ethics, compliance, and responsible AI principles

Can't prove AI value
KPI Development

AI metrics, success indicators, and executive dashboards

Teams resist AI adoption
Change Management

Workforce enablement and stakeholder alignment

Wrong tools get selected
Vendor Evaluation

AI platform and tool selection aligned with enterprise needs

AI budgets get cut
Investment Justification

Quantifying AI value, ROI, and mission impact for funding decisions

Can't prove AI value
KPI Development

AI metrics, success indicators, and executive dashboards

Teams resist AI adoption
Change Management

Workforce enablement and stakeholder alignment

Wrong tools get selected
Vendor Evaluation

AI platform and tool selection aligned with enterprise needs

AI budgets get cut
AI Investment Justification

Quantifying AI value, ROI, and mission impact for funding decisions

No roadmap for AI investment
AI Strategy Frameworks

Enterprise AI roadmapping, portfolio planning, and value prioritization

Wrong use cases get funded
Use Case Evaluation

ROI-driven assessment and prioritization of AI initiatives

Models fail in production
MLOps Principles

Model lifecycle management for scalable, production-ready AI

Compliance gaps create risk
AI Governance

Risk, ethics, compliance, and responsible AI frameworks

Validate Your AI Skills
HIGH-DEMAND INDUSTRIES

AI GOVERNANCE
LEADERS
EVERYWHERE

Every sector needs governance experts!

As AI regulations tighten globally, organizations need governance leaders who can ensure compliance, manage risk, and build trust. C|RAGE positions you at the center of responsible AI adoption.

Finance

AI risk management, auditing, trading governance, and fraud compliance enhance accountability.

Healthcare

Clinical AI governance, data privacy, and diagnostic accountability drive adoption.

Manufacturing

Predictive maintenance governance, quality control AI, and supply chain risk assessment improve operations.

Government

Public sector AI accountability and citizen services follow structured governance frameworks.

Technology

AI product governance, platform policies, and developer ethics fuel enterprise investment.

Disclaimer: The scenarios and impacts outlined above are based on indicative assumptions and high-level industry observations. Actual outcomes may vary by organization, regulatory context, and implementation maturity.

The solution is the same across every industry:

Trained & Certified AI Program Managers

AI Governance Hub

Policy & Compliance Center

Enterprise Ethics

Corporate AI Standards

Risk Management

AI Oversight Teams

Enroll in C|RAGE

CAREER OPPORTUNITIES

Job Roles C|RAGE Prepares You For

The C|RAGE certification opens doors to high-impact roles across AI governance, ethics, compliance, and leadership.

Executive & Leadership

  • Chief AI Officer (CAIO)
  • Chief Privacy Officer (CPO)/DPO
  • Technology Risk or Assurance Leader

Governance & Compliance

  • AI Compliance Managers/Officer
  • AI Governance Lead/Professional
  • Model Governance Specialist

Risk & Ethics

  • AI Risk Manager
  • AI Ethics Specialist
  • Legal, Ethical and Policy Advisor

Assurance & Audit

  • AI Auditor / AI Assurance Auditor
  • AI Assurance Specialist / Lead
  • Responsible AI Team Lead

Program & Lifecycle

  • AI Program Director/Manager
  • MLOps/AI Lifecycle Manager
  • AI Security Architect

Policy & Advisory

  • AI Policy Analyst / Advisor
  • Director AI Governance
  • Responsible AI Consultant
18+Job Roles

THE AI GOVERNANCE CRISIS

ORGANIZATIONS
CAN'T FIND
AI LEADERS

AI regulation is accelerating globally, but most organizations lack the governance expertise needed to stay compliant.

Enterprises need certified AI Governance professionals who can build ethical frameworks, ensure regulatory compliance, and manage AI risk across the organization.

Gartner predicts 75% of organizations will face AI compliance audits by 2027.1 McKinsey reports only 18% have formal AI governance in place.2

1 Gartner AI Governance Report, 2025 2 McKinsey AI Survey, 2025

The Governance Gap Organizations Face

  • Companies deploy AI, but lack governance frameworks to manage risk
  • Legal teams understand compliance, but can't translate AI technical risks
  • Data scientists build models, but don't own ethics accountability
  • Result: AI deployments without governance = regulatory exposure

What C|RAGE Validates

Verify the skills that make you the governance leader organizations need:

  • This credential validates your ability to lead AI governance programs
  • Verified skills in AI ethics, compliance, and risk management
  • Credential proves confidence advising executives on responsible AI
  • Industry-recognized proof of AI regulatory readiness
  • Validation that you can bridge the governance gap organizations need

What Your Organization Gets

Solve the AI governance crisis:

  • Establish AI governance before regulatory penalties arise
  • Build trust with customers through responsible AI practices
  • Align AI deployments with global compliance standards
  • Clear accountability frameworks for AI decision-making

AI GOVERNANCE LEADER SALARY DATA

What AI Governance Professionals Are Earning in 2026

As AI regulations intensify, governance expertise commands premium compensation. Certified AI Governance professionals who can navigate compliance are in high demand.

Source: Glassdoor, LinkedIn Salary Insights, Indeed, 2025–2026

Solve the problem, get paid!

$165K

Average Salary (US)

45K+

Open Positions

Responsible AI Specialist

$206,000

Median salary

Range: $155,000 – $279,000

Source: Glassdoor.com

Chief AI Ethics Officer

$379,500

Median salary

Range: $265,000 – $494,000

Source: Glassdoor.com

Director of AI Governance

$220,000

Median salary

Range: $190,000 – $250,000

Source: techjacksolutions.com

*Note All salary information is based on aggregated market data from publicly available sources and reflects US estimates. Actual salaries may vary based on location, education and other qualifications, skills showcased during the interview, and other factors.

Organizations offer premium compensation for professionals who can solve the AI failure problem. C|RAGE makes you that professional.
Become the Solution

C|RAGE PROGRAM FAQS

FREQUENTLY
ASKED
QUESTIONS

C|RAGE (Certified Responsible AI Governance & Ethics) trains governance professionals to lead AI oversight, ensure compliance, and build audit-ready programs. It’s aligned with the ‘Govern’ pillar of the ADG framework and prepares leaders to own responsible AI governance across the full AI lifecycle.

C|RAGE is designed for CISOs, GRC professionals, Data Protection Officers, AI Program Managers, Internal Auditors, and anyone responsible for AI governance, compliance, or policy in their organization.

The program covers NIST AI Risk Management Framework, ISO/IEC 42001, EU AI Act, GDPR/CCPA, SOC 2 Type II, and AI ethics and governance principles. You’ll master the frameworks that regulators and auditors expect.

C|RAGE focuses specifically on governance, compliance, and accountability, not technical AI skills. It’s designed for leaders who need to own AI oversight and build enterprise-scale governance frameworks, not for data scientists or engineers.

You’ll be able to build AI governance frameworks, ensure regulatory compliance, execute AI testing and auditing, manage AI risk assessment and third-party AI risk, and define enterprise AI strategy with authority.

No. C|RAGE is designed for governance professionals, not technical practitioners. You’ll learn enough about AI technology to govern it effectively, but the focus is on frameworks, compliance, and accountability.

C|RAGE is implementation-focused and audit-oriented.
It prepares professionals to design, document, operate, and defend AI governance programs in real enterprise environments, including accountability mapping, regulatory alignment, evidence generation, and assurance readiness.

Yes, C|RAGE is designed for global relevance and aligns with international AI governance, risk, and compliance frameworks, including widely adopted standards and regulatory expectations across regions.

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