Deploying Trustworthy Customer AI

This capstone unit prepares students to operationalize customer-facing AI and data products with attention to ethics, privacy, security, explainability, and organizational governance. Students synthesize prior technical skills and learn to evaluate trade-offs between profit, brand, and trust while designing human–machine collaboration and future-ready deployment strategies.

Learning Objectives

• Analyze deployment plans for customer-facing AI by identifying risks related to bias, privacy, security, and explainability and recommending mitigations using evidence from case studies
• Apply privacy, consent, and data-governance frameworks to design compliant data collection and retention workflows for a digital product scenario
• Demonstrate techniques to detect and mitigate model bias and to produce explainable outputs for stakeholders, using at least two model-agnostic and two model-specific methods
• Evaluate business trade-offs among profitability, brand reputation, and customer trust and produce a governance proposal and stakeholder presentation that justifies an AI deployment decision