Purpose of the Role
- Serve as the accountable leader for the AI portfolio strategy and industrialization.
- Turn experiments into adopted products with controlled costs, governance, and decision-grade evidence.
- Operationalize a single door model to replace ad hoc tools with a consistent, scalable AI product factory.
Portfolio Scope
A) AI Use Cases (through Innovation Board gates)
- Recipe.AI
- Chef.AI
- Portfolio.AI
- Marketing Translation
B) AI Center Enablement Services & Assets
- Innovation Board operating rhythm and gate criteria
- AI Lab Principles/Playbook (PoC → pilot → MVP → BAU)
- AI Toolkit + Sandbox adoption
- Ethics enablement
- FinOps/showback, cost governance, run cost strategy
Key Outcomes / Metrics of Success
- Roadmap & Investment Logic12-18 month portfolio roadmap with sequencing, dependencies, business cases, ROI, adoption assumptions. Clear prioritization based on value, feasibility, risk, and run cost.
- Innovation Board as a Product Factory Clear charter, RACI, cadence, scorecard, decision templates. Gate decisions supported by evidence: data readiness, evaluation plans, security posture, cost forecasts, adoption plan.
- Service Catalog Clarity AI Lab services with SLAs, artifacts, and volume forecasts. Toolkit/Sandbox as the standard experimentation route.
- Value Realization for BAU Products Quarterly reviews with funded optimization backlogs and measurable KPIs.
- Governance Scaled Distinguish PoC → pilot → MVP → GA. Done means standards include release readiness, telemetry, and operational handover.
- FinOps / Run Cost Control Maintain cross-charging model and GPU/compute strategy. Proactive budget and cost management.
- Singapore Government Co-Funding Success Maintain co-funding deliverables, KPIs, milestones, and reporting. Produce audit-ready evidence packs and manage stakeholder expectations.
Core Responsibilities
- Portfolio Strategy & Prioritization Define product strategy, adoption plans, KPIs, operating models. Manage trade-offs: value, feasibility, risk, time-to-market, run cost.
- Governance & Operating Model Own Innovation Board mechanics: gate criteria, decision logs, scorecards. Enforce definition of done standards: data/model contracts, security, BAU handover.
- Stakeholder Leadership Align with CDAO, Enterprise Architecture, R&D, Marketing. Own executive-ready decision packs (trade-offs, costs, risks, adoption constraints).
- Vendor & Partner Shaping Translate roadmap into outcome-based requirements and KPIs. Ensure vendor delivery meets industrialization standards. Define joint success measures with partners.
- Adoption, Ethics & Community Flywheel Drive enterprise adoption (ethics hub, Copilot/GenAI guidance, playbooks).Measure adoption via telemetry and feedback loops to inform roadmap.
Key Interfaces
- AI Lab
- Enterprise Architecture
- Platform & Security
- Finance / FinOps
- R&D & Marketing leadership
- Vendors & ecosystem partners (universities/startups)
- Singapore government co-funding stakeholders
Competencies & Skills
- Proven AI/digital product management track record (roadmaps, business cases, scaled adoption).
- Comfortable with enterprise governance: service catalogs, security-by-design, operational readiness.
- Skilled in commercial & partner shaping: outcome framing, KPI design, requirement clarity.
- FinOps/unit economics mindset: cost-to-serve, GPU/compute trade-offs.
- Executive communication: concise, decision-ready deliverables.
- Strong external stakeholder management (government co-funding programs, audits).
EA Number: 11C4879
