Strategic Leadership with AI and ML
Enhance your understanding of artificial intelligence and build your leadership credibility by taking the course offered by Singapore Management University.
Online
17 Weeks
2,500 USD Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Course Overview
The course titled AI-led Business Strategies focuses on the integration of Artificial Intelligence (AI) technologies and strategies into various aspects of business operations. The course aims to equip participants with the knowledge and skills required to leverage AI effectively to enhance business performance, drive innovation, and gain a competitive edge in the market.
The programme is tailored for professionals seeking to enhance their understanding and broaden their expertise in AI and its practical applications within business contexts and strategies. AI-led Business Strategies certification by Emeritus is a 2-month intensive course delivered online. It requires the participants to dedicate 4-6 hours each week. The programme caters to professionals who have a desire to further their knowledge and expertise in AI, focusing on its implementation in business scenarios and strategies.
The AI-led Business Strategies certification course is offered by the Singapore Management University. The course includes 8 modules of live teaching, along with assignments, case studies, industry examples and discussion boards to provide participants with a comprehensive learning experience. Participants will have access to real-world industry examples and world-class faculty.
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The Highlights
- 2-Month Programme
- 4-6 Weekly Hours
- Online Curriculum
- Offered by SMU
- 8 Modules
Programme Offerings
- Case Studies
- Industry Projects
- Live lessons
- Discussion boards
- assignments
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Singapore Management University, Singapore |
The AI-led Business Strategies certification fees is US$ 2000. The specified fees is exclusive of GST.
Fee Structure
Course Name | Fees |
AI-led Business Strategies | US$ 2000+ GST |
Eligibility Criteria
Certification Qualifying Details
Upon successful completion of the AI-led Business Strategies classes, a digital smart certificate issued by Singapore Management University is provided to the candidate.
What you will learn
After completing the AI-led Business Strategies certification syllabus, participants will be well-equipped with the basic and complex fundamentals of artificial intelligence and machine learning and their application in business. They will explore various business use cases where AI can be applied, such as customer engagement, marketing, sales, supply chain management, and operations optimization.
Furthermore, by completing the AI-led Business Strategies online course, they will be introduced to various ML algorithms used for data analysis, prediction, and decision-making in business contexts. Participants will understand how AI and ML algorithms can assist in making data-driven business decisions, such as pricing, resource allocation, and risk assessment.
Additionally, AI-led Business Strategies training will delve into the significant role of AI in automating mundane and repetitive tasks that consume valuable time and resources within business operations. By leveraging AI technologies, the participants will discover how to streamline and optimize various business processes, increasing overall efficiency and productivity.
Who it is for
By taking the AI-led Business Strategies online course, professionals from a wide range of industries can benefit in their careers. Professionals involved in multiple fields can take advantage of the course material in the programme. Some of the professionals who can benefit from taking this course are:
The Syllabus
- 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.
Instructors
Singapore Management University, Singapore Frequently Asked Questions (FAQ's)
The course is delivered in online mode.
The total duration of the programme is 2 months.
No experience in programming is required.
The programme is suitable for professionals in various industries who want to upskill their careers.
The course consists of 8 modules.