Responsible Deployment of Customer AI

This unit prepares students to operationalize customer-facing AI and analytics responsibly, covering deployment strategies, governance, and the human impacts of automation. Students will examine ethics, privacy, bias, explainability, security, and stakeholder trade-offs to design accountable, trust-preserving customer solutions.

Learning Objectives

• Analyze ethical, privacy, and bias risks in customer AI use cases and propose measurable mitigation and consent strategies aligned with regulatory and organizational requirements
• Apply explainability, monitoring, and bias-detection techniques to model outputs and document remediation plans and transparency communications for customers and stakeholders
• Demonstrate the ability to design a deployment and governance plan that includes security controls, accountability structures, board-level briefings, and incident response procedures
• Evaluate trade-offs between profitability, brand reputation, and customer trust and create stakeholder-aligned recommendations for human–machine collaboration and responsible product rollouts