How can one best put AI and Data Science to work in a modern company effectively to drive maximum value? Leaning on the emerging theory and best practices, we will examine companies at various sizes and stages and real-life cases to understand how companies should leverage AI, data science and machine learning to build a competitive advantage. We will draw similarities and contrasts between regular technology and data-science-heavy companies in terms of management, technical risks, and economics, and more. The students will learn how to reason about the cost and benefits of building up a data science capability within a company and how to estimate the value creation through data and AI from the perspective of investors. We will also have several AI founders and investors share their experience.
3 units · GSB Letter Graded
How can one best put AI and Data Science to work in a modern company effectively to drive maximum value? Leaning on the emerging theory and best practices, we will examine companies at various sizes and stages and real-life cases to understand how companies should leverage AI, data science and machine learning to build a competitive advantage. We will draw similarities and contrasts between regular technology and data-science-heavy companies in terms of management, technical risks, and economics, and more. The students will learn how to reason about the cost and benefits of building up a data science capability within a company and how to estimate the value creation through data and AI from the perspective of investors. We will also have several AI founders and investors share their experience.
Offered in Spring 2027 at Stanford University.