AI Adoption Workshop for Business Leaders (AI-AIBL)

Prerequisites:

Target Audience:

• This program is targeted at all decision makers from C suite to line management.

Course Objectives:

• Understanding AI
• Business Application of Generative AI
• Prompt Engineering 
• AI Projects (Exercise)

Course Outline:

Understanding AI (Day one Morning half day)

• Introduction to Generative AI
  • Definition and Overview
  • Historical Context and Evolution
  • Key Benefits and Applications in Business
• Core Concepts of AI
  • How Deep Learning enhances Machine Learning 
  • Natural Language Processing (NLP)
  • Computer Vision
  • Data Requirements and Management
• Ethics and Governance in AI
  • Ethical Considerations
  • Bias and Fairness
  • Transparency and Explainability
  • Regulatory Landscape and Compliance
• Tools and Technologies
  • Overview of Popular AI Tools and Platforms
  • Cloud vs. On-Premises Solutions
  • Case Studies of Successful Implementations
• Leadership and Change Management
  • Leading AI Initiatives
  • Building an AI-Ready Culture
  • Training and Upskilling Employees
  • Managing Resistance and Ensuring Adoption
  • Preparing for Continuous Change

Business Application of Generative AI (Day one Afternoon (1/2 day)

• AI Strategy and Implementation
  • Identifying Business Use Cases
  • Building an AI Roadmap
  • Integration with Existing Systems
  • Measuring ROI and Success Metrics
  • Company Wide Use cases for AI:
    • Customer Service and Support
      • Chatbots and Virtual Assistants: Automate customer interactions, provide 24/7 support, and handle common queries.
      • Personalized Recommendations: Enhance customer experience by offering tailored product or service suggestions.
    • Marketing and Sales
      • Content Generation: Create marketing materials, social media posts, and personalized email campaigns.
      • Market Analysis: Use AI to analyze market trends, customer sentiment, and competitor strategies.
    • Product Development
      • Design and Prototyping: Generate design concepts and prototypes quickly, reducing time-to-market.
      • Innovation: Use AI to identify new product opportunities and optimize existing products.
    • Operations and Supply Chain
      • Predictive Maintenance: Anticipate equipment failures and schedule maintenance proactively.
      • Inventory Management: Optimize stock levels and reduce waste through demand forecasting.
    • Human Resources
      • Talent Acquisition: Automate resume screening and candidate matching.
      • Employee Engagement: Use AI to analyze employee feedback and improve workplace satisfaction.

AI Project Planning and Implementation Module

• Identifying Business Objectives
  • Define clear, measurable goals for the AI project.
  • Align AI initiatives with overall business strategy and objectives.
• Feasibility Assessment
  • Evaluate the technical and financial feasibility of the AI project.
  • Conduct a risk assessment and identify potential challenges.
• Developing an AI Roadmap
  • Outline the project timeline, key milestones, and deliverables.
  • Assign roles and responsibilities to team members.
• Implementation and Monitoring
  • Execute the AI project according to the roadmap.
  • Continuously monitor progress, measure performance against KPIs, and make necessary adjustments.

Prompt Engineering Module for Business Leaders (Day Two – full Day)

• Introduction to Prompt Engineering
  • Definition and Importance
    • What is prompt engineering?
    • Why is it crucial for leveraging AI effectively?
• Real-World Examples
  • Case studies of successful AI implementations using prompt engineering.
• Basics of Crafting Effective Prompts
  • Understanding Prompts
  • What are prompts and how do they work?
  • Components of a Good Prompt
    • Clarity: Ensuring the prompt is clear and unambiguous.
    • Context: Providing enough context for the AI to understand the task.
    • Specificity: Being specific about the desired outcome.
• Common Pitfalls and Best Practices
  • Avoiding Vague Prompts
    • Examples of vague vs. clear prompts.
  • Iterative Improvement
    • How to refine prompts based on AI responses.
  • Testing and Validation
    • Techniques for testing prompts to ensure they yield the desired results.
• Hands-On Exercise: Generating Project Ideas
  • Step-by-Step Guide
    • Step 1: Identify Business Challenges
      • List current challenges or areas for improvement within the organization.
    • Step 2: Brainstorm AI Applications
      • Think of ways AI could address these challenges (e.g., automating tasks, enhancing customer experience).
    • Step 3: Craft Initial Prompts
      • Create initial prompts for AI tools to explore these applications.
    • Step 4: Refine and Test Prompts
      • Refine the prompts based on initial AI responses and test their effectiveness.
    • Step 5: Evaluate Feasibility
      • Assess the feasibility of the AI projects based on the refined prompts and potential ROI.
    • Group Activity: Collaborative Prompt Engineering
      • Form Small Groups
        • Divide participants into small groups to encourage collaboration.
      • Group Exercise
        • Each group selects a business challenge and follows the step-by-step guide to generate AI project ideas.
      • Presentation and Feedback
        • Groups present their project ideas and receive feedback from peers and facilitators.
      • Wrap-Up and Next Steps
        • Summary of Key Takeaways
        • Recap the importance of prompt engineering and best practices.
      • Action Plan
        • Encourage participants to apply what they’ve learned to real-world scenarios in their organization.