Objective: Learn how to structure and deliver compelling AI project proposals tailored to MTN Ghana’s needs, using effective presentation tools and techniques.

  • Proposal Structure:
    • Problem: Clearly define a telecom challenge (e.g., high customer churn in Mobile Money).
    • Solution: Propose an AI-driven approach (e.g., churn prediction model).
    • AI Approach: Specify tools, algorithms, or datasets (e.g., logistic regression with customer data).
    • Expected Impact: Quantify benefits (e.g., 10% churn reduction, cost savings).
    • MTN-Specific Example: A proposal to enhance Zigi chatbot with NLP to handle Twi queries, improving rural customer satisfaction by 15% (hypothetical metric).
  • Tools:
    • PowerPoint/Google Slides: Create slides with clear visuals (e.g., charts showing churn trends, diagrams of AI workflows).
    • Other Tools: Google Colab for demo code snippets, Canva for infographics.
    • Example: A slide deck with a problem statement (e.g., Mobile Money fraud), solution (anomaly detection), and impact (reduced fraud losses).
  • Tips for Effective Proposals:
    • Clear Visuals: Use graphs to show data trends (e.g., network traffic spikes).
    • Telecom Relevance: Align with MTN’s goals (e.g., 5G expansion, customer retention).
    • Feasibility: Ensure solutions are practical within MTN’s resources and Ghana’s infrastructure.
    • MTN Context: Proposals should address MTN Ghana’s priorities, like Mobile Money security or 5G rollout in Accra.
  • Benefits:
    • Prepares participants to pitch AI solutions to MTN leadership.
    • Ensures proposals are actionable and aligned with business needs.
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