An Interactive 5-Day Training Course

Artificial Intelligence (AI) Governance, Risk and Compliance

Building Responsible, Secure, and Accountable AI Frameworks for Modern Organisations

Artificial Intelligence (AI) Governance, Risk and Compliance

Scheduled Dates

08 - 12 Nov 2026
Riyadh - Saudi Arabia
$5,950
14 - 18 Dec 2026
Dubai - UAE
$5,950
10 - 14 May 2027
Amsterdam - The Netherlands
$5,950
26 - 30 Jul 2027
Dubai - UAE
$5,950
26 - 30 Jul 2027
Online
$4,950
06 - 10 Sep 2027
Doha - Qatar
$5,950
11 - 15 Oct 2027
London - UK
$5,950
08 - 12 Nov 2027
Riyadh - Saudi Arabia
$5,950
13 - 17 Dec 2027
Paris - France
$5,950

Why Choose this Training Course?

This Artificial Intelligence (AI) Governance, Risk and Compliance training course equips professionals with the knowledge and practical capabilities required to establish effective AI governance structures, manage AI-related risks and strengthen regulatory compliance across their organisations. As artificial intelligence becomes increasingly integrated into business operations and decision-making, organisations must establish clear accountability, effective oversight and appropriate controls throughout the AI lifecycle. Participants will examine how AI governance connects corporate policies, enterprise risk management and compliance obligations to support responsible AI development and deployment. The course emphasises structured governance arrangements that enable organisations to manage technological innovation while maintaining transparency, security and organisational accountability.

The training course examines international AI regulations, risk management frameworks, governance responsibilities and enterprise-wide compliance systems. Participants will explore the EU AI Act, the NIST AI Risk Management Framework and ISO/IEC 42001, alongside practical approaches to identifying algorithmic risks, implementing controls and monitoring AI system performance. Particular attention is given to AI risk registers, model approval processes, documentation requirements, cybersecurity integration and third-party AI governance. The training course also addresses assurance, audit readiness, organisational awareness and long-term governance maturity. By connecting regulatory expectations with practical governance and risk management processes, participants will develop a structured approach to implementing and maintaining effective AI governance, risk and compliance arrangements.

This Artificial Intelligence (AI) Governance, Risk and Compliance training course will highlight:

  • Establishing enterprise AI governance structures and accountability
  • Understanding AI regulations and compliance obligations
  • Identifying and managing AI-related operational and ethical risks
  • Developing AI policies, risk controls and approval procedures
  • Strengthening third-party AI oversight and compliance assurance
  • Building sustainable AI governance and risk management capabilities

What are the Goals?

By the end of this training course, participants will be able to:

  • Evaluate AI governance principles and organisational responsibilities.
  • Interpret relevant AI regulations and risk management frameworks.
  • Identify, assess and prioritise risks associated with AI systems.
  • Develop AI governance policies, accountability structures and controls.
  • Establish compliance monitoring, documentation and assurance processes.
  • Develop an enterprise AI governance, risk and compliance implementation roadmap.

Who is this Training Course for?

This training course is specifically designed for professionals directly responsible for AI governance, enterprise risk management, regulatory compliance and assurance activities, including:

  • AI Governance Managers and Officers
  • AI Risk Management Professionals
  • Governance, Risk and Compliance (GRC) Managers
  • Regulatory Compliance Managers and Officers
  • Enterprise Risk Managers responsible for AI risks
  • AI Assurance and Internal Audit Professionals
  • Model Risk Management Professionals
  • Legal and Regulatory Advisors responsible for AI governance
  • Information Security Governance Professionals responsible for AI systems

How will this Training Course be Presented?

This training course combines expert-led presentations, regulatory examples, AI governance scenarios and structured risk management exercises. Participants will examine AI risk registers, governance policies, compliance requirements and organisational oversight arrangements. Practical exercises will focus on identifying AI risks, evaluating existing controls, defining accountability and developing governance procedures. The methodology emphasises integrating AI governance with established enterprise risk management, compliance and assurance functions.

Organisational Impact

Organisations will benefit from:

  • Stronger governance and accountability for AI applications
  • Improved identification and management of AI-related risks
  • Greater preparedness for AI regulatory compliance
  • More consistent AI policies and control procedures
  • Stronger oversight of third-party AI systems
  • Improved AI assurance, transparency and audit readiness

Personal Impact

Participants will develop:

  • Greater understanding of enterprise AI governance requirements
  • Improved capability in AI risk assessment and mitigation
  • Stronger knowledge of AI regulatory compliance frameworks
  • Better understanding of AI policies and internal controls
  • Greater confidence in AI governance and assurance activities
  • Improved ability to develop organisational AI GRC strategies

Daily Agenda

Day 1: Foundations of AI Governance
  • Understanding AI technologies and enterprise impact
  • The need for structured AI governance and oversight
  • Key components of AI governance frameworks
  • Governance across the AI lifecycle
  • Roles and accountability in AI oversight structures
  • Assessing organisational readiness for responsible AI
Day 2: Regulatory Landscape and Compliance Obligations

  • Overview of global and regional AI regulations
  • EU AI Act: classifications and compliance obligations
  • NIST AI Risk Management Framework principles
  • GDPR implications for AI transparency and data protection
  • Documentation, auditability, and transparency requirements
  • Preparing for future AI regulatory developments
Day 3: AI Risk Identification, Assessment, and Mitigation

  • Identifying operational, ethical, legal, and societal risks
  • Detecting bias, unfair outcomes, and algorithmic harms
  • Risk scoring and prioritisation techniques
  • Ensuring transparency, explainability, and traceability
  • Mitigation controls across data, model, and deployment stages
  • Monitoring and evaluating AI system performance
Day 4: Building an Enterprise AI Governance System

  • Designing AI governance policies and procedures
  • Creating oversight committees and accountability structures
  • Documentation and reporting requirements
  • Model validation, approval processes, and audit trails
  • Integrating AI governance with cybersecurity controls
  • Ensuring compliance for third-party AI solutions
Day 5: Responsible AI Implementation and Future Readiness

  • Embedding responsible AI principles into organisational culture
  • Developing workforce awareness and governance capability
  • Managing AI-driven change and communication challenges
  • Aligning AI governance with ESG and organisational values
  • Preparing for internal and external AI audits
  • Developing a long-term AI governance maturity roadmap

Certificate

  • Upon successful completion of this training course, delegates will be awarded an official PetroKnowledge Certificate of Completion, signed by the course facilitator. The certificate confirms successful participation and records the total learning hours completed.
  • Continuing Professional Education credits (CPE): In accordance with the standards of the National Registry of CPE Sponsors, one CPE credit is granted per 50 minutes of attendance.

Accreditation

NASBA Approved Training Courses

Would an alternative date be more suitable?

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