As AI becomes integral to business operations, organizations must ensure it is deployed responsibly, securely, and in compliance with ethical and regulatory requirements. This workshop equips participants with the knowledge to govern AI confidently and mitigate organizational risks.

This course provides practical knowledge of AI ethics, governance frameworks, risk management, data privacy, bias mitigation, transparency, accountability, and responsible AI adoption.

  • Why get trained: Learn how to assess AI risks, develop governance frameworks, create AI policies, ensure regulatory compliance, and implement responsible AI practices across your organization.
  • Why it matters: Effective AI governance helps organizations maximize the benefits of AI while reducing ethical, legal, operational, and reputational risks, enabling sustainable and trustworthy AI adoption.
  • Who should attend: Executives, Senior Management, Board Members, Department Heads, Risk & Compliance Professionals, Internal Auditors, Legal Professionals, IT Managers, Data Governance Teams, Information Security Professionals, AI Engineers, Business Analysts, HR Professionals, Digital Transformation Teams, and Government Officers. Basically, anyone responsible for AI implementation or governance.

Gain the knowledge to establish responsible AI governance, manage AI risks, and lead ethical AI adoption across your organization. HRD Corp Claimable.

Overview

As Artificial Intelligence (AI) becomes increasingly embedded in business operations, decision-making, customer engagement, and public services, organizations must ensure that AI systems are developed, deployed, and governed responsibly. While AI offers significant opportunities to improve productivity, innovation, and competitiveness, it also introduces ethical, legal, regulatory, security, and reputational risks that require careful management.

This comprehensive two-day workshop provides participants with the knowledge, practical frameworks, and governance strategies needed to implement AI responsibly within their organizations. Participants will explore the principles of trustworthy AI, AI ethics, governance frameworks, risk management, regulatory considerations, data privacy, bias mitigation, transparency, explainability, accountability, and human oversight.

The program combines internationally recognized best practices with practical case studies, interactive discussions, governance exercises, and organizational planning activities. Participants will learn how to establish AI governance structures, develop AI policies, assess AI risks, evaluate AI systems, and promote responsible AI adoption across their organizations.

Designed for both public and private sector organizations, this HRD Corp claimable program equips leaders and professionals with the essential competencies required to govern AI confidently and ethically in today’s rapidly evolving digital landscape.

Skills Covered

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

  • Explain the importance of AI Ethics and Governance.
  • Identify common ethical issues in AI systems.
  • Assess AI risks across different business scenarios.
  • Recognize bias, discrimination, and fairness concerns.
  • Apply AI governance frameworks to organizational use cases.
  • Develop AI governance policies and best practices.
  • Evaluate AI systems for transparency and explainability.
  • Implement responsible AI principles within organizational workflows.
  • Improve AI compliance and risk management practices.
  • Build an AI governance roadmap for their organization.

Prerequisites

Participants should have:

  • Basic computer literacy
  • Basic understanding of digital technologies
  • Interest in AI adoption within organizations
  • No programming knowledge required
  • No prior AI experience required

Target Audience

This program is suitable for:

  • Senior Management
  • Executives
  • Board Members
  • Department Heads
  • AI Governance Committees
  • Risk Management Professionals
  • Compliance Officers
  • Internal Auditors
  • Legal Professionals
  • IT Managers
  • Data Governance Teams
  • Information Security Professionals
  • Data Scientists
  • AI Engineers
  • Business Analysts
  • HR Professionals
  • Digital Transformation Teams
  • Government Officers
  • Policy Makers
  • Anyone responsible for AI implementation or governance

Course Curriculum

Day 1

Module 1: Foundations of AI Ethics & Responsible AI

  • Introduction to Artificial Intelligence
  • Why AI Ethics Matters
  • Responsible AI Principles
  • Benefits and Risks of AI
  • Human-Centered AI
  • Trustworthy AI
  • Ethical Decision-Making
  • AI Opportunities vs AI Risks
  • Global AI Landscape

Hands-on Activities

  • AI ethics self-assessment
  • Discussion on real-world AI successes and failures
  • Interactive ethical dilemma scenarios

Module 2: AI Governance Frameworks & Standards

  • What is AI Governance?
  • AI Governance Lifecycle
  • Organizational AI Governance
  • AI Policies and Procedures
  • International AI Governance Trends
  • Overview of:
    • OECD AI Principles
    • UNESCO Recommendation on the Ethics of AI
    • ISO/IEC 42001 (AI Management System)
    • NIST AI Risk Management Framework (AI RMF)
    • EU AI Act (high-level overview)
  • Roles and Responsibilities
  • AI Governance Committees

Hands-on Activities

  • Mapping governance responsibilities
  • Governance framework comparison exercise

Module 3: AI Risk Management

  • Types of AI Risks
  • Operational Risks
  • Ethical Risks
  • Legal Risks
  • Cybersecurity Risks
  • Privacy Risks
  • Business Risks
  • Reputational Risks
  • AI Risk Assessment Process
  • Risk Register
  • Risk Mitigation Strategies

Hands-on Activities

  • AI risk identification workshop
  • Build a simple AI risk register

Module 4: Fairness, Bias & Explainability

  • Understanding AI Bias
  • Sources of Bias
  • Fairness Principles
  • Explainable AI (XAI)
  • Transparency
  • Accountability
  • Human Oversight
  • Responsible Decision-Making
  • AI Validation
  • Monitoring AI Outputs

Hands-on Activities

  • Analyze biased AI outputs
  • Improve AI prompts for fairness
  • Explainability exercise

 

Day 2

Module 5: AI Privacy, Security & Regulatory Compliance

  • AI Data Privacy
  • Personal Data Protection
  • Data Governance
  • Confidential Information
  • Intellectual Property
  • Copyright
  • AI Security Risks
  • AI Supply Chain Risks
  • Third-Party AI Services
  • Organizational Compliance

Hands-on Activities

  • AI data classification exercise
  • Privacy impact discussion
  • Secure AI usage scenarios

Module 6: Developing Organizational AI Policies

  • Responsible AI Policy
  • Acceptable AI Usage
  • Employee Guidelines
  • AI Procurement Considerations
  • Vendor Evaluation
  • AI Approval Process
  • Human Review Procedures
  • AI Documentation
  • AI Incident Reporting
  • Governance Roles

Hands-on Activities

Participants develop:

  • AI Acceptable Use Policy
  • AI Governance Checklist
  • AI Approval Workflow
  • AI Risk Review Template

Module 7: Responsible AI in Practice

AI Governance Across Business Functions

  • Human Resources
  • Finance
  • Procurement
  • Marketing
  • Customer Service
  • Healthcare
  • Education
  • Manufacturing
  • Government Services

Case Studies

  • AI hiring bias
  • Generative AI misuse
  • Deepfake incidents
  • Hallucinated business reports
  • Privacy breaches
  • AI governance success stories

Hands-on Activities

  • Analyze real-world AI governance cases
  • Group discussion on ethical decision-making
  • Recommend governance controls

Module 8: Building an AI Governance Roadmap

  • AI Readiness Assessment
  • AI Governance Maturity
  • Governance Operating Model
  • AI Committee Structure
  • Policy Implementation
  • Employee Awareness
  • AI Training Strategy
  • Monitoring & Continuous Improvement
  • KPIs for Responsible AI
  • Future Trends in AI Governance

Final Practical Exercise

Participants work in teams to design a high-level AI Governance Roadmap for a sample organization, including governance structure, policies, risk controls, oversight mechanisms, monitoring processes, and an implementation plan.

 

Dates & Locations

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Exam & Certification

Note: There is no exam directly associated with this course. However, Trainocate offers an extensive portfolio of industry-recognized certifications that can help you stand out as a tech professional in 2026 and beyond. Achieving these credentials are one of the most effective ways to validate your skills and accelerate your career.

With our expert-led training, you’ll be prepared to:

  • Master in-demand capabilities across Cloud, Data & AI, and Cybersecurity — areas driving global digital transformation.
  • Prove your expertise with a globally respected credential recognized by employers worldwide.
  • Advance your career by enhancing your credibility, increasing your earning potential, and opening doors to new opportunities.

Explore our full range of certs and start building the skills that matter today:

Trainocate Malaysia, based in KL Eco City, is proud to be an HRD Corp Registered Training Provider and a Yayasan Peneraju ALTI, driving workforce development across Malaysia.

Training & Certification Guide

Why train with Trainocate

This workshop adopts a highly interactive and practical learning approach through:

  • Instructor-led presentations
  • Interactive discussions
  • Real-world case studies
  • Group workshops
  • Scenario-based learning
  • Risk assessment exercises
  • Governance planning activities
  • Policy development exercises
  • Practical templates
  • Team presentations

Participants will gain experience in:

  • Identifying AI risks
  • Assessing ethical implications
  • Reviewing AI-generated outputs
  • Developing AI governance policies
  • Conducting AI risk assessments
  • Designing governance structures
  • Creating AI implementation roadmaps
  • Evaluating responsible AI practices

Participants will complete a short assessment to evaluate:

  • Understanding of AI concepts
  • Awareness of AI risks
  • Familiarity with AI governance
  • Knowledge of responsible AI principles
  • Organizational AI maturity

The assessment helps establish a baseline for measuring learning progress.

Participants will demonstrate their learning by:

  • Completing a knowledge assessment on AI ethics, governance, and risk management.
  • Participating in a scenario-based evaluation involving ethical and governance challenges.
  • Presenting an AI Governance Roadmap that includes governance structures, policies, risk controls, and implementation recommendations.

Receiving feedback on how to strengthen responsible AI practices within their own organizations

Upon completion, participants will have practical competencies in:

  • AI Ethics and Responsible AI
  • AI Governance Frameworks
  • AI Risk Management
  • AI Compliance
  • AI Policy Development
  • AI Accountability
  • Explainable AI (XAI)
  • AI Fairness and Bias Mitigation
  • Data Privacy and Security
  • AI Governance Strategy
  • Organizational AI Readiness
  • Responsible AI Leadership

Speak to a Training Consultant

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