Enterprise Ecosystems for Responsible Technology

This unit examines how historical technology waves and enterprise software innovation shape modern AI- and data-driven transformation across science, medicine, and business. Students assess ecosystem readiness, data treatment and governance, sustainability case studies, and strategies for reimagining leadership and choosing tech-for-good efforts that elevate brand and stakeholder value.

Learning Objectives

• Analyze key historical technology waves (e.g., personal computers, client/server, enterprise software) and synthesize their implications for contemporary AI, data-driven decision making, and sustainability initiatives within enterprises.
• Evaluate an organization’s ecosystem readiness for implementing AI-driven sustainability and transformation by assessing leadership structures, talent, data assets, partner networks, and governance, and recommend prioritized improvements.
• Apply data-treatment and governance best practices to a case study—including data quality, privacy, lineage, and compliance measures—to prepare datasets for ethical analytics and decision support.
• Demonstrate the ability to design a concise tech-for-good proposal that aligns with brand strategy and stakeholder needs by expanding the problem-solving table, integrating cross-functional roles (including a reimagined C-suite), and defining measurable impact metrics.