Cohort Module 1
Strategic AI portfolio framing
Executives learn to map generative and predictive AI opportunities against corporate strategy, capital allocation cycles, and competitive positioning. The module opens with a case discussion on a conglomerate deciding which of seven pilot projects deserve scale-up funding. Participants build a prioritisation matrix balancing revenue impact, regulatory exposure, and organisational readiness. Faculty introduce the syllabus arc vocabulary — cohort module, case discussion, leadership practicum — that structures the remainder of the programme. Pre-read materials include board memo templates and stakeholder interview guides used in live practicum preparation.
Cohort Module 2
Governance architecture for AI systems
Senior leaders design oversight structures appropriate to their industry context — model risk committees, data stewardship councils, and escalation paths to the board. Case materials examine a financial services group navigating MAS technology risk management expectations while piloting document automation. Participants debate where accountability should sit between CIO, CRO, and business unit heads. The module emphasises proportionate governance rather than checkbox compliance, preparing executives for regulator conversations and internal audit scrutiny without requiring legal qualifications.
Cohort Module 3
Operating model and vendor selection
This cohort module addresses build-versus-buy decisions, multi-vendor orchestration, and contract structures that preserve strategic flexibility. A case discussion centres on an enterprise choosing between a hyperscaler partnership and a specialised vertical AI vendor for customer operations. Participants evaluate total cost of ownership, data residency requirements under PDPA, and exit clauses. Leadership practicum preparation begins as executives draft vendor evaluation scorecards aligned to their own organisational procurement standards.
Cohort Module 4
Workforce transition and change leadership
AI adoption reshapes roles, skills requirements, and middle-management authority. Executives explore workforce planning frameworks that treat automation as a leadership challenge rather than an HR formality. Case materials follow a regional insurer redeploying underwriters alongside copilot tools. Participants practice difficult conversations — communicating role evolution to union representatives, setting realistic productivity expectations, and measuring adoption beyond vanity metrics. The module rejects life-coaching tropes in favour of structured change management grounded in organisational behaviour research.
Cohort Module 5
Board communication and stakeholder narrative
Directors and senior managers must translate technical AI concepts into risk-adjusted investment narratives that non-specialist board members can challenge intelligently. This module uses case discussion format to rehearse quarterly briefing structures, incident disclosure protocols, and competitive intelligence sharing boundaries. Participants receive peer feedback on clarity, defensibility, and alignment with fiduciary duties. Faculty highlight common presentation failures — overpromising capability, understating bias risk, and conflating pilot success with enterprise readiness.
Cohort Module 6
Leadership practicum and cohort debrief
The syllabus arc culminates in a leadership practicum where each executive presents a recommendation on a live challenge from their portfolio. Peers adopt adversarial board roles, probing assumptions and demanding evidence. Faculty assess decision quality, stakeholder mapping, and response to challenge — not technical accuracy of AI outputs. The cohort debrief consolidates learning themes and clarifies certificate issuance. Participants leave with actionable frameworks and a peer network of Singapore-based executives navigating similar AI transformation pressures across sectors.