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Digital Ethics and AI Governance for Leaders Duration: 1 Week/s

Course Information

  • Course Price £4895 Plus VAT
  • Location UK Courses
  • Course Code DEAI
  • Course Date 22 Jun - 26 Jun 2026

Course Objectives
Digital technologies and artificial intelligence are reshaping how organisations create value, manage risk, and interact with customers, employees, and citizens.
Alongside this opportunity, leaders face a growing set of ethical, regulatory, and reputational challenges that go far beyond traditional IT governance.
Stakeholders expect organisations to demonstrate not only compliance, but a visible ethical stance and robust governance over how data and AI are designed, deployed, and monitored.
Many boards and executive teams, however, struggle to ask the right questions about AI and digital ethics, to allocate clear accountability, and to embed governance frameworks that keep pace with innovation.
This intensive 5-day programme is designed for leaders who want to strengthen their capability to govern AI and digital technologies responsibly.
It brings together strategic management, risk, legal, technology, and ethics perspectives into a practical, leadership-focused framework.
Through case studies, simulations, and structured exercises, delegates will learn how to define ethical principles, shape governance arrangements, oversee high-risk AI use cases, engage stakeholders, and monitor ongoing compliance and performance.


Who should attend?
Leaders seeking to strengthen board-level discussion, documentation, and assurance on digital ethics and AI governance. Chief Digital Officers, Chief Data Officers, Chief Information Officers, Chief Technology Officers, and heads of innovation responsible for driving digital and AI transformation. Senior leaders who must align technical roadmaps with ethics, regulation, and enterprise risk appetite. Chief Risk Officers, Chief Compliance Officers, General Counsel, and Heads of Internal Audit responsible for governance, assurance, and regulatory relationships. Heads of AI, machine learning, analytics, and business intelligence who design and deploy data-driven systems and models. Technical leaders seeking a stronger connection between their work and board-level ethics, risk, and governance expectations. Senior managers identified as future leaders who will increasingly be involved in decisions on AI and digital transformation

Course Overview

Digital Ethics, AI, and the Strategic Landscape

  • Delegates will explore how AI and digital technologies are reshaping competition, public services, and stakeholder expectations.

  • Participants will examine major ethical debates and case examples where digital and AI failures have led to regulatory, legal, or reputational consequences.

  • They will learn to connect digital ethics and AI governance to overall strategy, brand, and trust.


    • Principles and Frameworks for Digital and AI Ethics

  • Delegates will review key ethical principles such as fairness, accountability, transparency, privacy, human oversight, and non-discrimination.

  • Participants will examine international frameworks, guidelines, and codes of practice for ethical AI and digital technologies.

  • They will learn how to translate high-level ethical principles into practical design criteria and governance guidelines.

    • Data Governance, Privacy, and Responsible Data Use
  • Delegates will examine the foundations of data governance, including data quality, lineage, access controls, and retention.

  • Participants will consider legal and regulatory requirements around privacy, consent, data protection, and cross-border data flows.

  • They will learn how decisions about data sourcing, sharing, and reuse impact digital ethics and AI risk.

    • AI Lifecycle, Risk Assessment, and Controls
  • Delegates will explore the AI lifecycle from problem definition and data selection through model development, deployment, and monitoring.

  • Participants will review methods for assessing AI risk, including impact assessments, model documentation, and testing for bias and robustness.

  • They will learn how to specify controls, thresholds, and escalation points for high-risk AI applications.

    • Governance Structures and Decision Rights for AI
  • Delegates will examine different models for AI governance, including committees, working groups, and federated approaches.

  • Participants will explore how to assign clear decision rights, accountabilities, and reporting lines for AI and digital initiatives.

  • They will learn how to integrate AI governance into existing structures for risk, compliance, technology, and product oversight.

    • Transparency, Explainability, and Stakeholder Communication
  • Delegates will explore expectations around transparency and explainability for AI systems in different stakeholder contexts.

  • Participants will learn how to communicate about AI use in ways that build trust with customers, employees, regulators, and the public.

  • They will examine approaches to documentation, disclosures, and responses to inquiries, challenges, or incidents involving AI systems.

    • Culture, Capability, and Ethical Leadership in the Digital Age
  • Delegates will examine how organisational culture, incentives, and leadership behaviours influence digital ethics and AI outcomes.

  • Participants will consider capability-building strategies for boards, executives, and staff on ethics, data literacy, and AI understanding.

  • They will learn how to model ethical leadership, encourage challenge, and create safe channels for raising concerns.

    • Road mapping, Metrics, and Continuous Oversight
  • Delegates will bring together insights from the programme to develop a roadmap for strengthening digital ethics and AI governance over the next 12–24 months.

  • Participants will explore metrics, dashboards, and reporting approaches that provide meaningful oversight without excessive complexity.

  • They will leave with a personal Digital Ethics and AI Governance Action Plan and a 90-day implementation focus.



    • Course Materials

    Course notes, handouts

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