1
Foundations of AI for Executive Strategy
Gain an understanding of the fundamentals of AI, ML, and DL, and how they are used in developing business strategies at the executive level.
Learning Outcomes
2
Learn AI Use-Cases Across Executive Strategizing
Identify strategic opportunities and operational use cases for AI across major business functions.
3
Evaluating AI Solutions
Evaluate feasibility and impact of AI initiatives, including data readiness, risks, and Return on Investment (ROI).
4
Practical AI Implementation
Lead AI adoption: set vision, roadmap, and metrics; manage change and capability building.
5
Ethics, Law & Privacy
Lead AI adoption: set vision, roadmap, and metrics; manage change and capability building.
6
Insights from Real-World Cases
Anticipate future AI trends and prepare the organization for disruption and continuous adaptation.
Program structure
Lesson Plan
5 modules • 51hours total length
Module 1: Executive Foundations of AI
Module 1: Executive Foundations of AI
What you'll learn
- Define AI, ML, and DL in business and executive terms
- Explain the AI value chain and its strategic implications
- Assess AI capabilities, limitations, and generative AI use cases
- Map AI to business objectives and organizational readiness
- Recognize myths, misconceptions, and regulatory requirements in AI adoption
Skills you'll gain
AI FundamentalsAI Value ChainGenerative AIOrganizational ReadinessStrategic Data UseAI LiteracyRegulatory Awareness
Module 2: Crafting an AI Strategy
Module 2: Crafting an AI Strategy
What you'll learn
- Link AI initiatives to long-term business vision and goals
- Identify and prioritize high-value AI opportunities
- Apply ROI frameworks to evaluate AI investments
- Decide on build vs. buy strategies for AI adoption
- Plan resources, talent, and vendor ecosystem for scaling AI
- Define metrics for AI success across transformation programs
Skills you'll gain
AI StrategyROI ModellingBuild vs BuyAI ScalingVendor ManagementTalent PlanningAI Success Metrics
Module 3: Governance, Ethics, and Risk Management
Module 3: Governance, Ethics, and Risk Management
What you'll learn
- Apply ethical AI principles of fairness, accountability, and transparency
- Detect and mitigate bias in AI decision-making systems
- Ensure compliance with GDPR, DPDP, and sectoral regulations
- Design governance structures and third-party audit processes
- Manage risks around cybersecurity, change, and crisis response
- Communicate AI ethics and governance frameworks to stakeholders
Skills you'll gain
Ethical AIBias MitigationRegulatory ComplianceAI GovernanceCybersecurityRisk ManagementStakeholder Communication
Module 4: AI Implementation Playbook
Module 4: AI Implementation Playbook
What you'll learn
- Select and execute AI pilot projects with agile methodologies
- Manage cross-functional teams for AI delivery at scale
- Design data and technology architecture for enterprise AI integration
- Evaluate vendor platforms and enterprise system compatibility
- Lead change enablement with training, adoption, and incentives
- Track AI performance and optimize post-deployment with case studies
Skills you'll gain
AI PilotsAgile AI DeliveryEnterprise IntegrationData ArchitectureVendor EvaluationChange EnablementPerformance Tracking
Module 5: Future of AI in Business Leadership
Module 5: Future of AI in Business Leadership
What you'll learn
- Analyze emerging trends such as quantum AI and autonomous agents
- Design strategies for AI-driven global supply chain optimization
- Build competitive advantage through AI moats and positioning
- Apply scenario planning for disruption and geopolitical AI risks
- Define the evolving role of CEOs and boards in AI-era leadership
- Prepare organizations for sustainable AI-first transformations
Skills you'll gain
Future TrendsQuantum AIAutonomous AgentsCompetitive AdvantageScenario PlanningAI LeadershipBoard Oversight
