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Module 07 · AI Leadership and Capstone Presentation
The AI Trust Pitch: From Data to Executive Buy-In
You are the AI Product Manager for 'SwiftConnect Telecom.' Your team built a model that predicts which customers will leave (churn). While the math is solid, the Executive Team is skeptical about 'black box' decisions and the Customer Service Lead fears the AI will replace their staff. You must pitch this project to get budget approval for a pilot launch.
45 minBeginner 3 outcomes 7 steps · 3 checkpoints
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Dataset
model_metrics_summary.csv
Summary of AI model performance and business impact — the raw 'technical' facts that need to be translated into an executive story.
Two rows contain technical jargon (F1, Neural Network) that learners must practice 'translating' for their pitch.
| metric_name(string) | current_value(string) | business_impact(string) |
|---|---|---|
| Model Precision (F1) | 0.88 | Identifies 8,800 at-risk customers accurately |
| False Positives | 12% | 1,200 customers might get unneeded discounts |
| Annual Churn Cost | $40,000,000 | The 'North Star' problem we are solving |
| Predicted Recovery | 15% | Potential $6M revenue saved |
| Model Type | Neural Network | Hard for non-tech stakeholders to understand |