Executive Education Program
AI Strategy for Enterprises
Course Description
- Gain a deep understanding of how AI is transforming enterprise strategy.
- Build a practical roadmap aligned with your business function and leadership role.
- Learn how to assess risks, opportunities, and governance requirements of enterprise AI.
Participant’s Profile
- Understand AI from a leadership and transformation lens.
- Explore real-world use cases across core business functions.
- Learn to align AI investments with enterprise value and risk.
- Build a practical AI Governance & Strategy playbook for your team or business unit.
Target Audience
- CxOs and Senior Executives
- Heads of Business Units (Sales, Ops, HR, Marketing, Finance)
- Strategy, Innovation, and Digital Transformation Leaders
- Legal, Risk & Compliance Owners involved in AI oversight
Modules
Module 1: Introduction to AI for Leaders
- What is AI? Definitions and types: Narrow AI vs General AI
- Subfields simplified: Machine Learning, Deep Learning, NLP, Computer Vision
- AI vs Automation vs Analytics – where does each fit in business?
Key Outcome: Leaders will confidently distinguish core AI capabilities and map them to their business needs.
Module 2: Why AI Matters for the C-Suite
- AI as a strategic tool for productivity, innovation, and competitive edge.
- When and how to invest – from pilot to enterprise scale.
- Economic Impact: Cost reduction, revenue growth, new business models.
- Balancing value creation with regulatory and reputational risks.
Key Outcome: Participants will be able to articulate AI’s value and risk in strategic planning discussions.
Module 3: Foundational AI Concepts (jargon-free)
- Data is the new oil – Why clean, governed data is AI’s foundation
- How machines learn – Supervised vs. unsupervised learning
- Neural networks & deep learning – High-level logic and why they matter
- Generative AI & LLMs – What they are, what they can do, and what they can’t
Key Outcome: Leaders will gain confidence discussing AI systems, model behavior, and data strategy with technical teams.
Module 4: Real-World Business Use Cases
- HR – Smarter Talent Acquisition & Engagement
- Marketing – Hyper-Personalized Campaigns at Scale
- Operations – Intelligent Automation of Workflows
- Across the Organization – Faster, Data-Driven Decision-Making
Key Outcome: Participants will walk away with a portfolio of potential AI applications tailored to their business function and goals.
Module 5: Risks, Ethics, and Governance
- AI Bias & Fairness – Detecting and mitigating unintended discrimination
- Transparency & Explainability – Why black-box AI is a boardroom risk
- Security & Privacy – Protecting data pipelines and preventing model misuse
- Regulatory Landscape – Overview of EU AI Act, NIST, ISO 42001, etc.
Key Outcome: Leaders will be equipped to define and oversee responsible AI policies and compliance actions.
Module 6: The Future of AI & Strategic Readiness
- Where AI is headed: Agentic workflows, multimodal models, real-time AI copilots
- C-suite readiness priorities: Talent, data, change management, governance
- What early adopters are doing now (case examples)
Key Outcome: Participants will craft their leadership action plan to advance AI maturity in their enterprise.