Programme Partner
Overview
AI isn’t coming. It’s compounding. The pilots are done.
The real question surrounding AI for senior executives is who will architect the advantage when intelligence becomes embedded across the enterprise?
This is where Strategic leadership with AI shifts from experimentation to orchestration, redefining capital allocation, competitive moats, and governance in an age of autonomous systems.
Singapore stands at the frontier of this transformation, pairing rapid innovation with world-class governance. It offers a living laboratory for leaders shaping an Enterprise AI Strategy that balances speed, scale, and accountability, from agentic ecosystems to sovereign AI capabilities.
Delivered by Singapore Management University—one of the few institutions in Asia to hold the prestigious "Triple Crown" accreditation (AACSB, EQUIS, and AMBA)— the Strategic Leadership with AI programme lays out the roadmap for AI for business leaders who are ready to move beyond adoption toward reinvention, building intelligent enterprises, redesigning operating models, and leading confidently into the algorithmic decade.
- Next Course Starts On 30 June 2026 (Tue)
- Duration17 Weeks, Online 4-6 hours per week
- VenueOnline
Learning Objectives
➤ Explain core AI, generative AI, and agentic AI concepts for enterprise leadership.
➤Evaluate risks, governance, and reliability of enterprise AI systems.
➤Assess enterprise-grade AI and agentic system architectures.
➤Identify, prioritise, and justify high-impact AI initiatives.
➤Evaluate and architect AI-enabled product, service, and business model transformations.
➤Lead AI strategy, implementation, and organisational transformation.
PROGRAMME HIGHLIGHTS
15 Cutting-Edge Modules
Learn AI strategy, LLMs, RAG, Agentic AI, governance and transformation.
Topics/Structure
- Understanding AI. Distinguish between traditional AI and Generative AI
- Historical overview of AI from traditional AI to Generative AI
- Demystifying Deep Learning for Business Leaders
- Neural Networks without the math
- Text generation and language models
- Understand AI and Large Language Models (LLMs)
- How GPT, Claude and Gemini work
- Capabilities and limitations of LLMs
- How and why training and LLM work, without the math
- Customising an LLM, via training and fine-tuning
- Evaluating the LLM after training or customising without training
- Deploying a customised LLM
- Understand RAG architecture and why it matters for enterprise AI
- Master vector databases, embeddings, and retrieval strategies
- Evaluate RAG system performance with key metrics
- Design and deploy RAG for your organisation
- What defines an autonomous AI agent
- Agent design: memory, planning, feedback loops
- Tool orchestration: APIs, LLMs, systems
- Multi-agent collaboration and coordination
- Strategic AI Opportunities in HR (talent, workforce planning, productivity)
- Strategic AI Opportunities in Finance (forecasting loops, risk, performance)
- Strategic AI Opportunities in Marketing & Sales (signals, orchestration, conversion)
- Strategic AI Opportunities in Supply Chain (forecasting, routing, exception handling)
- Cost vs Revenue Prioritisation for Functional AI Initiatives
- Designing Cross-Functional AI Workflows and Intelligence Loops
- Breaking Functional Silos Through Agent-Enabled Decision Flows
- Leadership Actions for Aligning Functional AI to Enterprise Transformation
- Gen AI and Agentic AI Applications in Marketing, Sales, and Customer Experience
- Enhancing Finance, Risk Management, and Supply Chain with AI and Agentic AI
- Leveraging AI and Agentic AI for HR Transformation and Talent Strategy
- Leading AI and Agentic AI Initiatives Across Business Functions
- Driving Operational Efficiency Through AI and Applied Agentic AI
- Transitioning to AI-Enhanced Services and Offerings
- Building Product-as-a-Service Models enabled by Intelligence Layers
- AI for Smarter Logistics, Inventory, and Adaptive Operations
- Scaling AI Across Products and Service Lines (platform architecture)
- Design for Hyper-Personalisation and AI-Augmented Product Innovation
- Agent-Based Recommendation Engines and Self-Optimising Delivery
- Designing Data Feedback Loops to Improve Products Continuously
- Industry-level GenAI use cases and competitive dynamics (Retail, CPG, BFSI, Manufacturing, Public Sector)
- Prioritisation frameworks for GenAI portfolio selection (value, feasibility, risk, data readiness)
- Enterprise integration patterns: RAG, retrieval quality, workflow orchestration, validation layers
- Model strategy: open-source, API, hybrid, sovereign cloud, on-prem trade-offs
- Data, infrastructure, and operational dependencies (security, latency, cost, compliance)
- Guardrails for accuracy and reliability (hallucination controls, sandboxing, quality gates)
- Governance alignment with local guidelines, compliance framworks and enterprise AI policies
- Enterprise roadmap: pilots → platform → scale; capability maturity and operating model choices
- AI as a Central Business Strategy
- Crafting an AI Vision and Strategic Narrative
- AI-Driven Business Model Reinvention
- AI Portfolio Strategy: where to play and how to win
- Agent-first Strategy: redesigning decision flows and leadership responsibilities
- Building strategic moats in the AI-driven economy
- Enterprise readiness for AI-led reinvention
- AI Value Chains and National Strategies
- AI as Narrative Amplifier (and Distorter)
- Weaponisation of AI Technologies
- Building Resilient, Sovereign AI Systems
- Practical Sovereignty for Corporates: What ‘Sovereign AI’ Means at the Enterprise Level
- Scaling AI Projects from Pilots to Enterprise Platforms
- Building a Robust Data Strategy for AI (quality, lineage, governance, accessibility)
- Operational Readiness for AI Deployment (integration, monitoring, security)
- Structuring AI Teams & Operating Models (CoE, federated, hub-and-spoke, platform)
- Cross-Functional Collaboration Models
- Measuring AI Success (ROI, KPIs, adoption, performance)
- Agent Lifecycle Management (monitoring, controlling, orchestrating autonomous systems)
- Leading Organisational Transformation in the Age of AI
- Fostering a Culture of Curiosity, Experimentation, and Psychological Safety
- Addressing Fear, Resistance, and AI Anxiety
- Communicating AI Initiatives with Clarity and Credibility
- Embedding AI into Change Programs and Leadership Rituals
- Redesigning Leadership Roles in Hybrid Human–Agent Organisations
- Building Trust in Agentic Systems: Transparency, Accountability, and Boundaries
- Designing AI-Augmented Teams and Hybrid Roles
- Preparing for Job Evolution in the Age of AI
- Building AI-Centric Upskilling and Reskilling Strategies
- Redesigning Performance and Talent Metrics for the AI Era
- Human–Agent Collaboration Models: AI as colleagues, not just tools
- Identifying and Mitigating AI Bias, Fairness, and Ethical Risks
- Navigating Privacy Regulations and Compliance in AI
- Promoting AI Transparency and Explainability
- Ethical risks in Agentic AI — runaway autonomy, decision accountability
- Establishing Effective AI Governance Frameworks
- Build a comprehensive AI strategy for a real-world business challenge in a 1-Week capstone project.
Who Should Attend
This Strategic Leadership with AI Programme is designed for forward-thinking professionals who recognise AI as the new operating system of business.
Senior Professionals: Leaders shaping organizational strategy and focusing on ROI, governance, and sustainable business models beyond the hype.
Mid-Career Professionals: Individuals seeking to pivot or drive operational excellence and focusing on practical frameworks, workflow redesign, and leading hybrid teams.
Technology & Transformation Leaders: Professionals bridging business and tech and focusing on deepening their understanding ofenterprise-grade architectures like RAG and Sovereign AI for scalable implementation.
15% Fee Waiver for SMU Alumni
Assessment
Schedule
Start Date(s) : Tue, 06/30/2026 - 12:00
Intake Information :
Refer to Online Singapore Management University Courses - Emeritus - Online Certificate Courses | Diploma Programs for the latest updates on application dates and discounts.
For more enquiries, please email to ur-opsteam-APAC@emeritus.org or ruswelt.pereira@emeritus.org.
Alternatively, you may also write to us at exd@smu.edu.sg for any urgent matters related to the programme.
COURSE FEE
US$ 2,500 +Applicable Taxes
*Singapore residents who wish to enrol for this programme will be charged GST.
*Applicable taxes will be charged at checkout.