University teaching · Executive education

AI teaching for business and technology

Tern Poh was an instructor and moderator in the NUS MBA Tech Club's AI for Business Leaders series. He also introduced AI at an NIE webinar for educators. Proposed topics connect business decisions, AI risks and the design of AI workflows.

Teaching areas

Proposed teaching areas and outcomes, to be matched to the course and learners.

Assess an AI business case

Learners

MBA, business and executive education learners

Learning outcomes

Define the decision and value an AI use case should support.
Identify gaps in data, team skills and delivery ownership.
Recommend whether to proceed, revise or stop a proposal.

Turn AI risks into design choices

Learners

Business and computing students; working professionals

Learning outcomes

Map the people affected by an AI system and its likely failures.
Assign responsibility for risk decisions and human review.
Compare controls for transparency, security and human oversight.

Design and test an AI agent workflow

Learners

Computing students and professionals building AI applications

Learning outcomes

Map the roles of models, tools and people in a workflow.
Define allowed actions and points for human approval.
Test a prototype against its task and likely failure cases.

Proposed sample lesson

Should this AI pilot proceed?

An illustrative lesson plan with a fictional scenario, prepared for discussion with course leaders.

Learners: MBA, business and executive education learners
Format: 60 minutes · discussion and group exercise · no coding required

Fictional scenario

A service team proposes an AI assistant that drafts replies from an approved knowledge base. Decide whether to run a pilot, what evidence is needed and which actions require human review.

Learner output

A one-page recommendation naming the business owner, one success test, one failure test and the human-review boundary.

Lesson outline

10 min Frame the business decision and its owner
15 min Assess data, skills and readiness gaps
15 min Define controls and failure tests
15 min Review the proposal in groups
5 min Present a proceed, revise or stop recommendation

Assessment criteria

Business decision: Names the decision, affected users, owner and expected value.
Readiness: Identifies specific gaps in data, skills and delivery ownership.
Controls: Links plausible failures to justified access limits and human review.
Recommendation: Uses testable criteria to justify proceeding, revising or stopping.

Past workshops and educator sessions

Instruction and moderation for MBA students, and an AI introduction for educators.

Workshop and panel moderation

AI for Business Leaders Workshop Series

NUS MBA Tech Club · 2023

Instructor and moderator in a three-part series on AI business use cases, ChatGPT prompt engineering and AI in industry

NUS Business School article

Educator webinar

AI4E - Developing AI Literacy Among Educators: Building an AI Model

National Institute of Education · 2020

Introduced AI at an NIE webinar for over 100 educators and school teachers; the session included a practical AI model demonstration

NIE article Webinar recording

Curriculum advisory

SUSS Academy · Industry Advisor

Since September 2026, an industry advisory appointment supporting curriculum, courseware, assessment and learner pathways in Continuing Education and Training.