Career Options

This course is a comprehensive introduction to the field of artificial intelligence (AI), tailored for graduate students with minimal prior background knowledge in AI or machine learning (ML).  The course focuses on foundational theories of AI, ethical and societal implications of AI technologies, and practical skills in using modern AI tools.  This is an interdisciplinary course appropriate for learners from all disciplines.

This course equips MBA students to manage AI capabilities in their organization to accelerate customer-centric growth. Students will examine AI-driven tools and martech techniques that enable businesses to identify market gaps, personalize experiences, understand customer behavior, and foster innovation through growth loops, data flywheels, value creation networks, and ROI frameworks. Marketing tasks such as customer segmentation, predictive analytics, content creation, and product development will be explored through case studies, hands-on experiences, and other practical exercises culminating in a final AI-enabled growth plan. Students will learn to leverage AI for strategic growth while maintaining ethical standards and data privacy.

This course empowers students to manage AI initiatives in their organization to transform business processes and supply chain operations using cutting-edge AI technologies. Students will explore how AI technologies such as predictive analytics, robotic process automation (RPA) and generative AI can be applied to enhance efficiency, optimize workflows, reduce costs, streamline logistics, and strengthen competitive positioning. Through case studies and experiential projects, participants develop practical AI strategies tailored to real-world business contexts such as automated inventory and demand forecasting, HR and finance processes, predictive maintenance, and logistics optimization, among others. A final AI-enabled business efficiency plan will demonstrate strategic AI business competency.

This course prepares MBA students to examine the ethical, legal, and policy challenges associated with the deployment of artificial intelligence within organizations. Students will explore issues such as algorithmic bias, accuracy limits and related liabilities, data privacy, intellectual property rights, and regulatory compliance. The curriculum blends accountability and ethical AI frameworks, stakeholder analysis, AI and data governance models, and regulatory impact assessments. Through case studies and hands-on exercises, students will learn to strategically navigate the complex landscape of AI and build strategies for accountable AI implementation in various industries across stakeholders and various ESG (Environmental, Social, and Governance) scenarios.