AI Governance for Business Leaders

The AI Governance for Business Leaders program is an executive development course offered by Monash University Malaysia to equip non-technical leaders with practical AI oversight capabilities. Delivered in-person at the Bandar Sunway campus over 2 days, this workshop relies on interactive lectures, real-world case discussions, and structured group exercises rather than formal graded assessments. The program is fully HRDCorp Claimable for eligible organizations.

Incentives available for groups and teams of four or more attending open enrollment programs

DOWNLOAD BROCHURE

This program is designed for mid-to-senior level managers, functional leaders, and decision-makers responsible for adopting, approving, procuring, operating, or assuring AI solutions. Key target roles:
- Data Protection Officers (DPOs) and Privacy Leaders
- Company Secretaries, Board Support, and Risk Committee Members
- Chief Risk Officers (CROs), Compliance, Legal, and Internal Audit Leaders
- Transformation, Strategy, Digital, and Innovation Leaders
- Operations, IT, Data, Procurement, and HR Heads across corporations, SMEs, GLCs, and public bodies
- Financial regulators and central bank professionals
- Non-Technical AI Clarity: Learn key AI concepts and distinguish conventional machine learning, generative AI,and agentic AI to pinpoint business, legal, and reputational exposures without needing a technical or coding background.
- Pre-Approval & Procurement Oversight: Gain confidence in asking the right questions to technical teams and vendors before approving, procuring, or deploying AI systems.
- Regulatory & Framework Compliance: Master local and international regulatory frameworks—including Malaysia's National Guidelines on AI Governance and Ethics, 2026 PDPC guidelines, the proposed AI Governance Bill, Bank Negara Malaysia, Securities Commission expectations, ISO/IEC 42001, and NIST AI RMF.
- Risk & Failure Management: Proactively manage risks like hallucinations, data leakage, shadow AI, IP/copyright issues, prompt injection, bias, overreliance, and autonomous AI agents.
- Practical Governance Outputs: Depart with ready-to-use organizational tools, including:
  - An AI use-case inventory and risk register
  - A Governance RACI matrix across business, tech, risk, legal, and audit roles
  - A human review protocol for automated decisions
  - An AI Acceptable Use Policy
  - A board/management reporting template
  - A customized 90-day AI governance action plan
Program Content
The course is delivered across 5 core modules over 2 days:
- Module 1: Introduction to AI and Its Relevance for Decision Makers Focuses on essential AI knowledge for leaders. Distinguishes conventional machine learning, generative AI, and agentic AI, alongside their business impacts, legal exposures, and reputational risks.
- Module 2: Understanding AI Models: What They Are and How They WorkCovers pre-approval essentials: AI lifecycles, data dependencies, model limitations, foundation models,vendor/outsourced systems, Data Protection Impact Assessment (DPIA) triggers, and critical vendor questions.
- Module 3: Explainable AI: Tools to Understand and Trust Model OutputsLeverages explainability as a governance control. Focuses on transparency, documentation, decision challenge,audit trails, recourse, monitoring, and human review protocols for automated decisions under the 2026 PDPC guidelines.
- Module 4: AI Risks, Failures, and Ethical ChallengesAddresses generative AI hazards (hallucinations, shadow AI, IP, prompt injection, bias) and dedicated governance of AI agents (autonomy tiers, action logs, human-in-the-loop, and emergency stop mechanisms).
- Module 5: Governance and Regulatory Approaches for Responsible AIThe practical synthesis module. Applies Malaysian guidelines, PDPA, the proposed AI Governance Bill,BNM/SC expectations, ISO/IEC 42001, and NIST AI RMF to participants' own organizational use cases to draft policies, RACI matrices, and board reports.
Ir. Dr. Manjeevan Singh Seera
- Role & Affiliation: Associate Professor, School of Business, Monash University Malaysia
- Qualifications: PhD in Computational Intelligence (Universiti Sains Malaysia); Registered Professional Engineer
- HRDCorp Trainer Number: 16092
- Profile: Dr. Manjeevan is an accomplished academic and industry expert specializing in machine learning,predictive analytics, AI governance, and sustainable technology solutions. He brings extensive experience delivering executive training for financial institutions, regulatory bodies, and corporate leaders—bridging the gap between complex technical AI capabilities and strategic oversight.

Session 2-1-1 Block

2027 Session

11 - 12 January 2027

START:: 11th January at 9 a.m.
END:: 12th January at 5 p.m.
FORMAT:: In-person at Monash University, Bandar Sunway Campus, Kuala Lumpur, Malaysia

Education and Training Academy

Education and Training Academy

AI Governance for Business Leaders