Certificate in AI Governance

AI Governance Training Course is essential for organisations adopting artificial intelligence while striving to ensure transparency, fairness, accountability, and compliance. As AI systems increasingly influence decisions across business, government, and society, the need for well-defined governance structures has never been more critical. This course provides a comprehensive foundation for understanding how to supervise AI responsibly and how to align AI initiatives with organisational strategy, ethical expectations, and emerging regulations.

This AI Governance Course guides participants through practical governance frameworks, global regulatory trends, and the ethical principles that underpin trustworthy AI. Using the outline for context, the course explores models such as the EU AI Act, ISO/IEC 42001, and the NIST AI Framework, enabling participants to evaluate risks, establish governance roles, conduct AI impact assessments, and ensure transparency in AI-driven operations. Participants learn how to recognise risks such as bias, privacy concerns, and lifecycle vulnerabilities that must be addressed when implementing AI.

Throughout the AI Governance Training Course, delegates review case studies of real-world governance failures, analyse the challenges associated with modern AI systems, and develop policies that support ethical, compliant, and value-driven AI adoption. By combining expert insights with hands-on exercises, the course prepares participants to lead AI governance efforts, support responsible innovation, and build organisational readiness for future regulatory and technological developments.

By the end of this AI Governance Course, participants will understand the essential tools, standards, and methodologies required to build responsible AI systems and governance structures. They will learn how to evaluate AI risks, align governance models with organisational strategy, and implement frameworks that ensure fairness, transparency, and accountability throughout the AI lifecycle. The course also emphasises compliance with emerging regulations, documentation requirements, and the use of global standards to oversee AI systems effectively.

More specifically, participants will be able to:

• Understand core principles of AI governance, ethics, and responsible AI.
• Develop and implement governance frameworks aligned with organisational goals.
• Identify and mitigate AI-related risks including bias, privacy, and safety issues.
• Apply global standards such as the EU AI Act, NIST AI Framework, and ISO/IEC 42001.
• Build governance policies that support transparency, fairness, and accountability.
• Conduct AI risk assessments, audits, and lifecycle evaluations.
• Establish governance roles, responsibilities, and oversight structures.
• Support trustworthy and compliant AI adoption across multiple industries.
• Lead ethical, sustainable, and value-based AI implementation.

This AI Governance Training Course is designed for professionals responsible for overseeing AI initiatives, ensuring compliance, or guiding responsible innovation within their organisations. It is ideal for leaders and specialists who must design governance structures, manage AI-related risks, or supervise ethical and regulatory obligations associated with AI technologies.

It will greatly benefit:

• Chief Officers (CTO, CIO, CDO), Directors, and Senior Managers.
• AI and Data Governance Professionals.
• Risk, compliance, and internal audit teams.
• Policy makers and public-sector officials.
• AI/ML engineers transitioning into governance roles.
• Digital transformation leaders overseeing AI deployment.
• Legal and regulatory affairs specialists.
• Anyone responsible for AI ethics, oversight, or responsible innovation.

This AI Governance Training Course uses a blend of interactive and practical learning methods to ensure knowledge retention and real-world application. Participants engage in guided discussions, instructor-led sessions, and structured exercises focused on AI governance challenges.

Participants can expect:

• Lecture-led content covering governance models, regulations, and ethical principles.
• Group discussions analysing AI governance needs across industries.
• Case studies of governance failures and regulatory impacts.
• Workshops on regulatory assessment, risk evaluation, and policy development.
• Hands-on exercises focused on bias analysis, transparency, and governance design.

This approach ensures participants leave prepared to establish strong AI governance processes and lead responsible AI initiatives within their organisations.