AI-Driven Personalization & Data Ethics

This unit examines the data, models, and ethical considerations that enable effective AI-driven personalization and improved customer experiences. Students will evaluate data quality and sources, compare personalization approaches (including generative AI), and design practical workflows such as automated routing and agent support to boost satisfaction.

Learning Objectives

• Analyze internal and third-party data sources and assess data quality, suitability, and contextual constraints for use in customer analytics and personalization
• Evaluate ethical, privacy, and legal considerations (including non-consumer customer contexts) to determine appropriate data governance and limits on personalization
• Apply contemporary AI-based personalization methods—including model selection and generative AI techniques—to choose personalization targets and justify those choices based on business goals and contextual factors
• Design an automated customer experience workflow (e.g., message routing, agent support, or interpretation layers) that integrates models with operations and identifies implementation challenges beyond model development