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Why this Certification Matters

AI CERTs
Enables Integrated Assurance Across Functions

Empowers audit, risk, compliance, and governance teams to work in sync using AI, eliminating silos, reducing duplicated efforts, and ensuring comprehensive organizational risk coverage.

AI CERTs
Strengthens AI-Driven Risk Visibility

Equips professionals to leverage AI for continuous monitoring, real-time dashboards, and intelligent insights, helping detect overlaps, gaps, and emerging risks faster and more accurately.

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Improves Reliance and Coordination Decisions

Teaches assurance leaders how to use AI-assisted mapping and analytics to evaluate testing quality, rely on other providers’ work, and optimize resources while maintaining governance standards.

AI CERTs
Enhances Governance, Compliance, and Control

Builds deep understanding of global AI governance frameworks like ISO/IEC 42001, NIST AI RMF, EU AI Act, and IIA standards to ensure secure, ethical, and compliant assurance practices.

AI CERTs
Builds Trust Through Responsible AI Practices

Promotes transparency, human oversight, and ethical AI deployment, enabling organizations to deliver reliable assurance outcomes and strengthen stakeholder confidence in AI-enabled decisions.

AI Enabled Coordinated Assurance Certification
Duration

8 hours

Prerequisites

No mandatory prerequisites. However, a foundational understanding of AI concepts, risk management, audit or compliance processes, and familiarity with assurance or governance frameworks is recommended.

Outcome

Participants will gain an executive-level understanding of how AI enables coordinated assurance across audit, risk, compliance, and governance functions. They will learn to leverage AI for assurance mapping, reduce duplication of efforts, enhance cross-functional collaboration, strengthen model integrity and security controls, and align assurance practices with global governance standards such as ISO/IEC 42001, NIST AI RMF, EU AI Act, and IIA Standard 9.5.

AI CERTs

Who Should Attend?

  • Chief Audit Executives & Internal Audit Leaders: For CAEs and audit heads driving integrated assurance strategies and aligning audit functions with AI-enabled coordination and IIA Standard 9.5.

  • Risk & Governance Professionals: Ideal for risk managers and GRC leaders seeking to unify risk insights, eliminate assurance overlaps, and strengthen enterprise-wide governance using AI tools.

  • Compliance & Regulatory Officers: Designed for professionals responsible for meeting ISO, NIST, EU AI Act, and other regulatory requirements through automated monitoring and coordinated reporting.

  • Assurance & Control Owners: Perfect for teams across internal audit, compliance, cybersecurity, and vendor risk who collaborate to map coverage, reduce duplication, and improve reliance decisions.

  • AI & Security Architects: Targeted at technology and AI security leaders implementing secure, trustworthy AI systems with strong model integrity, continuous monitoring, and enforcement controls.

Industry Growth – AI Enabled Coordinated Assurance

01

The global assurance, risk, and compliance landscape is rapidly evolving as organizations adopt AI to streamline audit, risk, and governance functions. Enterprises are shifting from siloed assurance models to integrated, AI-enabled approaches that improve efficiency, transparency, and real-time risk visibility.

02

Internal audit and risk teams are increasingly leveraging AI technologies such as NLP, machine learning, and automation to reduce duplicated testing, enhance data integration, and enable continuous monitoring—driving faster audits and smarter decision-making across functions.

03

Regulatory pressure and global governance standards—including ISO/IEC 42001, NIST AI RMF, and emerging AI regulations—are accelerating demand for coordinated assurance frameworks that ensure compliance, accountability, and defensible AI use across the enterprise.

04

Organizations are prioritizing collaborative assurance models aligned with the Three Lines framework and IIA standards, enabling audit, compliance, and risk teams to share insights, optimize resources, and strengthening enterprise-wide risk coverage through AI-driven mapping and reliance strategies.

05

As AI systems grow more complex and embedded in critical operations, the need for structured, AI-enabled coordinated assurance programs is expanding—creating strong demand for specialized training, certifications, and tools that support secure, ethical, and scalable governance practices.

What You'll Learn

AI CERTs

AI-Driven Assurance Coordination

Learn how AI integrates audit, risk, and compliance functions to eliminate silos, reduce duplication, and enable seamless collaboration across assurance teams.

AI CERTs

Intelligent Risk & Coverage Mapping

Understand how AI-powered assurance mapping detects overlaps, identifies gaps, and provides a unified view of organizational risks for stronger, data-backed decisions.

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Automated Monitoring & Reporting

Discover how AI enables continuous monitoring, real-time dashboards, and automated reporting to accelerate insights, improve transparency, and enhance governance outcomes.

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Secure & Compliant AI Operations

Build expertise in applying AI governance frameworks, policy enforcement, and model integrity controls to ensure systems remain secure, auditable, and regulation ready.

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Responsible & Collaborative Assurance Leadership

Develop the leadership skills to drive cross-functional alignment, foster trust, and implement ethical, AI-enabled assurance practices that strengthen accountability and organizational resilience.

Certification Modules

  1. 1.1 Foundations and Importance of Coordinated Assurance
  2. 1.2 Roles of Assurance Providers and Stakeholders in Coordinated Assurance
  3. 1.3 Standard 9.5 and Governance Expectations
  1. 2.1 AI’s Impact on Data Integration and Communication
  2. 2.2 Overview of Key AI Technologies for Assurance
  3. 2.3 Collaboration Use Cases Enabled by AI
  4. 2.4 Risk in AI Utilization
  1. 3.1 Identifying Overlaps and Gaps with AI
  2. 3.2 Introduction to Integrated Assurance Mapping
  3. 3.3 Reliance Strategies and AI
  1. 4.1 Securing AI Systems Post-Deployment
  2. 4.2 Model Integrity and Auditing
  3. 4.3 Cryptographic Integrity Protections (Hash Validation & Signature Rotation)
  4. 4.4 Side-Channel Attack Scenarios on Model Checkpoints, Quantized Models, and GPU Memory
  5. 4.5 Guardrail Testing Patterns for Automated Prompt Sanitization
  6. 4.6 Separation of Duties & Dual Control for High-Risk AI Models
  7. 4.7 Evaluation Guidance for Model Behavior Consistency
  8. 4.8 RSAIF Mapping, GRC Interpretation, and Evidence Requirements
  9. 4.9 Introducing Dual Lab Paths and a Tools Capability Matrix
  10. 4.10 Hands-On: Implementing RBAC for Secure AI APIs (Dual Lab Path)
  11. 4.11 Knowledge Check
  1. 5.1 Case Study – Implementing AI in Coordinated Assurance
  2. 5.2 Introduction to Ethical Considerations in the Case Study
  3. 5.3 Overview of Case Outcomes
  1. 6.1 Introduction to AI Security Tools
  2. 6.2 Automating AI Security and Compliance
  3. 6.3 Hallucination Monitoring and Scoring Mechanisms
  4. 6.4 Architecture of Automated Compliance Pipeline
  5. 6.5 Automated Rollback Workflows, Drift Alerts, and Scheduled Red Teaming
  6. 6.6 Cross-Model Validation for Multi-Model AI Systems
  7. 6.7 GPU Runtime Observability and Isolation Requirements
  8. 6.8 Introduction: AI Security Automation Stack
  9. 6.9 Expanding AI Security Tool Categories
  10. 6.10 Tool Selection Criteria and Capability Matrix
  11. 6.11 Real Automation Workflow & Evidence Generation
  12. 6.12 Hands-On Lab
  1. 7.1 AI Governance Frameworks and Controls (in Coordinated Assurance)
  2. 7.2 Trust, Transparency, and Ethics in AI-Enabled Assurance
  3. 7.3 Measuring Assurance Effectiveness (Metrics, KRIs, KPIs, and Continuous Improvement)
  4. 7.4 Conclusion and Next Steps

Program Design and Approach: A Strategic Framework for AI-Enabled Coordinated Assurance

AI CERTs
  • Comprehensive Overview: Introduces AI-enabled coordinated assurance by integrating audit, risk, governance, and compliance through automation. Learn how AI improves collaboration, risk visibility, and oversight.
  • Designed for Assurance Professionals: Built for auditors, risk and compliance leaders. Streamline activities, cut duplication, and apply standards like ISO/IEC 42001 and National Institute of Standards and Technology AI RMF.
  • Real-World Application: Covers AI-driven mapping, automated reliance, continuous monitoring, and coordinated reporting to reduce gaps and strengthen decisions.
  • Collaborative Learning: Case studies, simulations, and labs build skills in data integration, communication, and evidence sharing across teams.
  • Actionable Takeaways: Leave with ready-to-use frameworks, tools, and workflows to implement scalable, transparent, AI-powered assurance.

Ready to Transform Assurance with AI?

Enroll in the AI-Enabled Coordinated Assurance Program to integrate AI across audit, risk, compliance, and governance. Reduce duplication, boost collaboration, automate mapping, and make smarter, data-driven decisions.

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Frequently Asked Questions

Yes. The program focuses on practical applications of AI in audit, risk, compliance, and governance. You’ll work with real-world use cases, assurance mapping exercises, and automation workflows that can be implemented in your organization right away.

Unlike traditional courses that treat audit and risk functions separately, this program emphasizes coordinated assurance powered by AI. It teaches you how to integrate teams, eliminate duplicated efforts, and align with global standards such as ISO/IEC 42001, NIST AI RMF, and the EU AI Act.

You’ll engage in hands-on activities like AI-driven assurance mapping, reliance analysis, automated compliance checks, shared dashboards, and evidence generation. Case studies simulate real organizational challenges to help you practice coordinated, AI-enabled decision-making.

The course blends expert-led sessions, interactive discussions, real-life case studies, tool demonstrations, and hands-on labs. This balanced approach ensures you not only understand the concepts but also apply AI tools and frameworks in realistic assurance environments.

By mastering AI-enabled coordination strategies, you’ll strengthen your ability to lead cross-functional assurance initiatives, improve governance transparency, and drive efficiency across your organization, positioning you as a forward-thinking assurance and risk leader.