Introduction

Artificial intelligence is increasingly embedded in organisational decision-making, automation, and operational processes, often without corresponding clarity around governance, accountability, and oversight. While AI can enhance efficiency and insight, weak governance structures can expose organisations to regulatory, ethical, reputational, and operational risks. Leaders are now accountable not only for outcomes driven by human decisions, but also for those influenced or executed by AI-enabled systems.

This Governing AI Use in the Organisation training course focuses on governing AI use from a leadership, governance, and risk perspective rather than technical implementation. It examines how accountability shifts when decisions are automated or augmented, where oversight frequently breaks down, and how leaders can design effective control and escalation mechanisms.

Key focus areas include:

 

Key Learning Outcomes

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

Training Methodology

This training course adopts a governance-focused, scenario-driven learning approach tailored for leaders and decision-makers. Participants engage with real organisational cases, applied governance frameworks, and structured oversight exercises that reflect practical accountability challenges. The methodology emphasises critical judgement, peer discussion, and applied analysis rather than technical detail, enabling participants to translate learning directly into leadership and governance practice.

Governing AI Use in the Organisation

Who Should Attend?

This training course is ideal for professionals seeking to…

  • Board members and non-executive directors
  • Senior executives and C-suite leaders
  • Risk, compliance, and governance professionals
  • Internal audit and assurance leaders
  • Technology and digital oversight executives
  • Public-sector leaders with accountability for AI-enabled services

Course Outline

Day 1

Oversight, Risk, Accountability and Control

  • How AI changes decision-making
  • Where accountability becomes unclear
  • Leadership responsibilities for AI use
  • Common governance blind spots
  • Regulatory and ethical expectations
Day 2

Oversight and Control of AI Systems

  • Oversight models for AI-enabled processes
  • Human oversight and escalation
  • Control design and access management
  • Monitoring performance and outcomes
  • Managing third-party AI risk
Day 3

Risk Identification and Impact Assessment

  • Operational, ethical, and reputational risk
  • Bias, transparency, and explainability
  • Data quality and decision integrity
  • Incident management and response
  • Audit and assurance considerations
Day 4

Embedding Responsible AI Governance

  • Policies, standards, and governance forums
  • Accountability mapping for AI decisions
  • Integrating AI into risk frameworks
  • Training leaders and managers
  • Reporting and assurance mechanisms
Day 5

Sustaining Effective AI Governance

  • Reviewing and updating governance models
  • Managing AI evolution and scale
  • Board reporting and oversight
  • Lessons learned from failures
  • Personal governance action planning

International Standards & Professional Alignment

Our training courses are aligned with internationally recognised professional standards and frameworks across leadership, strategy, finance, governance, risk, compliance, and audit. By integrating globally trusted models, we ensure learners develop practical, relevant, and industry-recognised capabilities.

Our trainings draw on leading international standards and professional frameworks, including ISO, ISACA, COSO, OECD, IIA, FATF, Basel, IFRS/ISSB, GRI, NIST, CPD, ILM and the OECD AI Principles. This alignment ensures consistency with global best practices across financial management, risk oversight, digital governance, sustainability, and strategic decision-making..

Designed in alignment with globally recognised professional bodies, our courses support continuous professional development, strengthen organisational capability, and provide clear pathways toward professional certifications valued worldwide.

Ready to Take the Next Step?

Reserve your slot today and start your learning journey with us.

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FAQs

AI systems increasingly influence decisions that carry legal, financial, and reputational consequences. Governance leaders are accountable for outcomes regardless of whether decisions are made by people or systems, making oversight, accountability, and control essential leadership responsibilities.  

No. This training course is designed for non-technical leaders and focuses on governance, accountability, and risk oversight rather than system design or coding. Technical complexity is translated into leadership-relevant considerations.  

AI can obscure decision ownership, dilute responsibility, and complicate escalation when outcomes are automated or distributed across systems. Without deliberate governance design, accountability can become unclear and difficult to defend.  

The course addresses governance, ethical, operational, reputational, regulatory, and accountability risks, including bias, transparency failures, weak oversight, third-party AI exposure, and incident response challenges.  

Participants learn how to document accountability, design controls, and establish oversight mechanisms that stand up to regulatory review, audit scrutiny, and external challenge.  

Yes. The training course explicitly addresses board and executive responsibilities, reporting structures, escalation mechanisms, and governance models required for effective AI oversight at senior levels.  

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