AI Adoption for Strategic Management

Course Outline

1. Introduction to AI in Strategic Management

• Meaning and evolution of Artificial Intelligence
• AI vs Automation vs Machine Learning
• Why AI matters for modern strategy
• AI as a source of competitive advantage
• Overview of AI adoption across industries

2. Strategic Management Fundamentals (AI Context)

• Vision, mission, and strategic objectives
• Internal and external environment analysis
• AI-enhanced strategic planning
• Role of data in strategy formulation
• Strategic decision-making models

3. AI Technologies for Strategic Use

• Machine Learning and Deep Learning
• Natural Language Processing (NLP)
• Computer Vision
• Predictive Analytics
• Generative AI (Chatbots, LLMs, copilots)
• AI platforms and ecosystems

4. AI and Competitive Advantage

• AI-driven value creation
• Cost leadership vs differentiation using AI
• AI in Porter’s Five Forces analysis
• AI-enabled Blue Ocean strategies
• Sustaining advantage in AI-first organizations

5. AI in Environmental and Industry Analysis

• AI for PESTLE analysis
• Market and competitor intelligence using AI
• Customer behavior analytics
• Trend forecasting and scenario planning
• Strategic foresight with AI tools

6. Data Strategy and AI Readiness

• Data as a strategic asset
• Data governance and quality
• AI maturity models
• Build vs Buy vs Partner decisions
• Assessing organizational readiness for AI

7. AI in Corporate Strategy

• AI in growth strategies (market penetration, diversification)
• Mergers & acquisitions and AI due diligence
• Platform strategies and ecosystem building
• Global strategy and AI localization
• AI-driven innovation strategies

8. AI in Business-Level Strategy

• AI in marketing strategy (personalization, pricing)
• AI in operations and supply chain strategy
• AI in finance and risk management
• AI in HR and talent strategy
• AI in customer experience management

9. AI, Leadership, and Change Management

• Strategic leadership in the AI era
• Managing AI-driven organizational change
• Human–AI collaboration
• Workforce reskilling and upskilling
• Culture, trust, and adoption barriers

10. Ethical, Legal, and Governance Considerations

• AI ethics and responsible AI
• Bias, fairness, and transparency
• Data privacy and protection regulations
• AI governance frameworks
• Strategic risk of AI misuse

11. Measuring Strategic Impact of AI

• AI KPIs and performance metrics
• ROI of AI investments
• Balanced Scorecard with AI integration
• Strategic control systems
• Continuous improvement using AI insights

12. AI Strategy Implementation

• AI roadmaps and implementation models
• Pilot projects vs enterprise-wide adoption
• Vendor selection and partnerships
• Integration with legacy systems
• Scaling AI solutions

13. Industry Case Studies

• AI strategy in Technology firms
• AI adoption in Banking and Finance
• AI in Healthcare strategy
• AI in Manufacturing and Logistics
• AI strategy in Public Sector and SMEs

14. Future of AI in Strategic Management

• Emerging AI trends
• Autonomous organizations
• AI and strategic resilience
• Long-term societal and business impacts
• Preparing for AI-driven disruption

15. Capstone Project

• AI readiness assessment of an organization
• Development of an AI-enabled strategic plan
• Risk and ethics evaluation
• Final presentation and defense

Learning Outcomes

By the end of the course, learners will be able to:

• Integrate AI into strategic planning and execution
• Evaluate AI technologies for strategic value
• Lead AI-driven transformation initiatives
• Address ethical and governance challenges
• Measure and sustain AI-enabled competitive advantage