• AI basics and key concepts

• Types of AI and capabilities

• AI ecosystem and use cases

• Ethics concerns and risks

• AI governance principles & objectives

• Governance structures & roles

• Policies, procedures & decision rights

• Responsible AI by design

• AI system life cycle overview

• Data governance in AI

• Model development & validation

• Monitoring, evaluation & continuous improvement

• AI risk identification & assessment

• Risk treatment & mitigation

• Bias, fairness & model robustness

• Risk monitoring & reporting

• Global AI regulations overview

• EU AI Act — key provisions

• National AI strategies & laws

• Compliance obligations

• ISO 42001 AI Management System

• NIST AI RMF framework

• Standards, tools & best practices

• Audit, assurance & accountability

• Ethical principles in AI

• Fairness, transparency & explainability

• Privacy, security & data protection

• Ethical leadership & culture

Understand core AI concepts, governance principles, structures, and roles, and embed responsible AI by design from the outset of any AI initiative.

Identify, assess, and treat AI risk, and apply practical techniques for detecting and mitigating bias to strengthen model fairness and robustness.

Navigate global AI regulations and the EU AI Act's key provisions, alongside national AI strategies, laws, and compliance obligations.

Work with ISO 42001 and the NIST AI Risk Management Framework, and apply standards, tools, and best practices for audit, assurance, and accountability.

Apply ethical principles, fairness, transparency, and explainability, and build the privacy, security, and data protection practices that sustain trust.

Assess governance maturity, build a strategy and roadmap, lead change management and adoption, and establish KPIs for continuous oversight.

CAIG is a governance-focused certification from Digital Union, designed for leaders and professionals ready to shape ethical, transparent, and compliant AI ecosystems.

Leaders and professionals responsible for AI governance, risk, compliance, legal, and ethical AI practice within their organizations.

You will learn AI governance principles and frameworks, AI risk management and bias mitigation, global and national AI legal frameworks including the EU AI Act, techno-legal standards such as ISO 42001 and the NIST AI RMF, ethics in corporate governance, and AI governance strategy and implementation.

Basic knowledge of IT and Operations, along with completion of a pre-class assignment sent by the facilitator.

The course is structured across three phases: Aware (foundations), Arise (framework and policy), and Enlight (advanced leadership).

Eight core modules spanning AI essentials, AI system and governance framework, the AI development life cycle, AI risk management, global and national AI legal frameworks, techno-legal standards and practices, AI ethics in corporate governance, and AI governance strategy and implementation.

Yes. The course covers global and country-specific frameworks, including the EU AI Act's key provisions, ISO 42001, and the NIST AI Risk Management Framework.