AI Use Cases: Adding and Maintaining Value
summary
Companies split use cases by management level and map concrete projects: an operational chatbot ~1,000 calls/day using NLU/transformers, a tactical churn model predicts users leaving in six months that classifies at-risk customers, and a strategic regression forecasting feeding executive spreadsheets. Building needs labeled data, ETL and governance, PII removal, monitoring for data drift, and an MLOps stack — Airflow, Databricks, Kubernetes — because POCs work but production succeeds only with pipelines, model registry, CI/CD and ongoing support.
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chapters (11)
- 0:00Intro
- 2:55Split management across three levels
- 4:14Split management within a company
- 5:14Three levels of management
- 6:17Example
- 8:18Differences
- 12:35Matrix
- 18:53Common Perception
- 20:23caveats
- 23:29data
- 27:08ML ecosystem
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