Enterprise AI & Gen AI Strategy
Executive Course Bootcamp
This immersive bootcamp equips leaders with strategic, technical, and operational understanding of Generative AI and its transformative business potential. Through executive-focused discussions, real-world case studies, and practical hands-on activities, participants will learn how to identify AI opportunities, develop AI-enabled business strategies, manage organizational transformation, and responsibly scale AI initiatives across enterprises.
Executive Education
Inspired Course
Duration
24 hours
Session Days
Weekdays
Weekends
Course Delivery
Classroom
Live Remote
Target Audience
Leaders, C-Level Executives, Directors, Heads
Level
Strategic: Advanced
Technical: Intermediate
Cost
USD 299
* For corporate group training rates contact helpline
Bootcamp Features
Generative AI is rapidly reshaping industries, redefining competitive advantage, and transforming how organizations innovate, operate, and engage customers. Executives who understand AI strategy and execution are better positioned to drive growth, improve decision-making, optimize operations, and future-proof their organizations. This domain is critical because organizations increasingly require leaders who can align AI adoption with business objectives while addressing governance, ethics, workforce transformation, and enterprise-scale implementation challenges.
Why to Learn AI & Gen AI Strategy Development?
What Skills Will You Learn?
Who is this Course For?
Curriculum
| Topics | Practical Work |
|---|---|
| ▸ Evolution of Artificial Intelligence ▸ What is Generative AI? ▸ Difference between AI, ML, Deep Learning, and Generative AI ▸ Business implications of Generative AI ▸ Industry trends and market outlook ▸ Key AI terminology for executives | ▸ Exploring Generative AI platforms ▸ Executive AI readiness self-assessment ▸ AI use case brainstorming activity |
| Topics | Practical Work |
|---|---|
| ▸ AI-driven business disruption ▸ AI and competitive advantage ▸ Business model innovation through AI ▸ Industry case studies (Finance, Healthcare, Education, Retail, Manufacturing) ▸ AI-first organizations | ▸ Industry disruption mapping exercise ▸ Competitive AI analysis workshop ▸ AI business opportunity canvas ▸ SWOT and Business Model Canvas |
| Topics | Practical Work |
|---|---|
| ▸ Responding to AI disruption strategically ▸ Defensive vs. offensive AI strategies ▸ AI maturity models ▸ Change management in AI transformation ▸ Building resilience in AI-enabled enterprises | ▸ AI risk-opportunity matrix ▸ Organizational AI maturity assessment ▸ Transformation readiness workshop |
| Topics | Practical Work |
|---|---|
| ▸ How Large Language Models (LLMs) work ▸ Neural networks and transformers ▸ Tokens, embeddings, and context windows ▸ AI infrastructure and cloud ecosystems ▸ AI economics and cost structures ▸ Build vs Buy decisions | ▸ Demonstration of LLM workflows ▸ Token analysis activity ▸ AI cost-benefit analysis exercise |
| Topics | Practical Work |
|---|---|
| ▸ Prompt engineering principles ▸ AI content generation workflows ▸ AI for communication and productivity ▸ AI for business analysis and reporting ▸ Multimodal AI systems ▸ AI automation basics | ▸ Prompt engineering exercises ▸ AI-generated presentations and reports ▸ AI-assisted business proposal development ▸ Building custom GPT workflows |
| Topics | Practical Work |
|---|---|
| ▸ AI-assisted executive decision-making ▸ Predictive analytics and forecasting ▸ Scenario analysis using AI ▸ Data-driven leadership ▸ AI-powered business intelligence | ▸ AI-assisted forecasting exercise ▸ Executive dashboard analysis ▸ Business decision simulation |
| Topics | Practical Work |
|---|---|
| ▸ AI strategy frameworks ▸ Identifying high-value AI opportunities ▸ Prioritizing AI initiatives ▸ AI value chain analysis ▸ AI roadmap development | ▸ AI strategy canvas workshop ▸ Enterprise AI roadmap design ▸ Use case prioritization exercise |
| Topics | Practical Work |
|---|---|
| ▸ AI pilot design ▸ Scaling AI initiatives ▸ AI operating models ▸ AI Center of Excellence (CoE) ▸ Enterprise AI transformation lifecycle | ▸ AI pilot planning activity ▸ AI transformation roadmap development ▸ Scaling strategy workshop |
| Topics | Practical Work |
|---|---|
| ▸ AI talent requirements ▸ Upskilling and reskilling strategies ▸ Building AI culture ▸ Cross-functional AI teams ▸ Leadership competencies for AI transformation | ▸ AI workforce capability mapping ▸ Organizational capability gap analysis ▸ AI leadership competency assessment |
| Topics | Practical Work |
|---|---|
| ▸ Common AI adoption barriers ▸ Resistance to change ▸ AI implementation failures ▸ Stakeholder management ▸ AI success metrics and KPIs | ▸ AI adoption case analysis ▸ Failure analysis workshop ▸ Success KPI design activity |
| Topics | Practical Work |
|---|---|
| ▸ AI governance frameworks ▸ Responsible AI principles ▸ AI bias and fairness ▸ Privacy, security, and compliance ▸ Regulatory considerations | ▸ AI ethics case discussions ▸ Governance framework design exercise ▸ AI risk assessment activity |
| Topics | Practical Work |
|---|---|
| ▸ AI and the future of work ▸ Human-AI collaboration ▸ Workforce transition strategies ▸ Ethical workforce transformation ▸ Building sustainable AI organizations | ▸ Workforce transformation planning ▸ Human-AI collaboration scenarios ▸ Responsible AI leadership reflections |
| Project Activities | Deliverables |
|---|---|
| ▸ Develop an AI transformation strategy for a selected organization Identify opportunities, risks, governance, and implementation roadmap ▸ Present AI execution strategy to executive review panel | ▸ AI Strategy Canvas ▸ Enterprise AI Roadmap ▸ AI Governance and Risk Plan ▸ Transformation Presentation |