From AI to FinTech: Inside New MBA Courses at Tuck

With a particular emphasis on generative AI, the new courses span ground-breaking topics and timely challenges facing business and leaders today.

Tuck offered 18 exciting, new MBA elective courses in its 2023-2024 academic year. The new courses cover a wide range of timely and ground-breaking topics: from fintech and investing in early-stage social ventures to leading diverse teams and qualitative investing. But there is one clear, standout topic among the new courses: artificial intelligence. 

Joe Hall, senior associate dean for teaching and learning, emphasized the intentionality behind integrating AI into Tuck’s curriculum. “This academic year, we’re especially focused on bringing the latest in generative AI into the classroom, but that’s just the tip of the iceberg,” says Hall, who is also the David T. McLaughlin D’54, T’55 Clinical Professor. “We’ve added new courses and are integrating pedagogical methods that not only equip students with a deep understanding of AI’s role in business and society, but also offer them hands-on practical application of the technology.”

Three of the new AI-focused courses are: the elective Optimization Modeling for Prescriptive Analytics taught by new professor James Siderius; the research-to-practice seminar AI-Driven Analytics and Society, also taught by Siderius; and the sprint course AI and Consultative Decision-Making taught by Clinical Professor Scott Anthony D’96. Last academic year, Tuck also added multiple courses on AI, including Generative AI and the Future of Work and the marketing course AI for Managers.

Siderius, who joined the Tuck faculty last year, says his new courses focus on the complexities of generative AI, urging future managers to look beyond the allure of data and algorithms and grapple with the ethical imperatives of fairness, bias, and transparency.

“Avoiding the classic pitfalls of AI isn’t just about smart management—it’s about conscientious leadership,” says Siderius. “When you’re dealing with traditional analytics tools, transparency is a given. But with machine learning, we enter a more opaque world.”

The courses also tackle the far-reaching impact of generative AI on the job market and society. Siderius shares how large language models, though remarkable in their capabilities, carry the risk of misinformation due to inherent biases. “They speak with great confidence and often they’re wrong. Knowing when and why AI can err is crucial for our students who will soon be decision-makers,” Siderius says.

Sonya Mishra, assistant professor of business administration at the Tuck School of Business at Dartmouth, is taking a scientific approach to tackling workplace gender inequity.

Several new courses are also aimed at addressing crucial societal and organizational challenges facing leaders today. Leading Diverse Organizations with Assistant Professor of Business Administration Sonya Mishra; Women, Gender, and Leadership in the New Workplace with Clinical Professor Stacy Blake-Beard; and Equity Analytics in Organizations with Assistant Professor of Business Administration Julia Melin; are all designed to foster inclusive leadership skills, while Moral Reasoning with Josh Lewis encourages students to explore the ethical complexities in business decisions.

Tuck’s research-to-practice seminars and practicums offer students hands-on experiences that bridge academic research with real-world application. The “Investing in Early-Stage Social Ventures” practicum taught by professors Curt Welling D’71, T’77 and Ramon Lecuona, for example, provides students the opportunity to assess the potential of early-stage ventures with social impact.

Without further ado, here are Tuck’s new MBA courses for the 2023–2024 academic year.


AI and Consultative Decision-Making (Sprint)
Scott Anthony D’96

Decisions. Scholars suggest individuals make 2,000 a day. Large organizations make exponentially more. Many of these decisions are low stakes, straightforward, day-to-day decisions that are safely made automatically. Some are high stakes, complex, once-in-a generation decisions. Amazon’s Jeff Bezos calls these Type 1 decisions, which he defines as “consequential and irreversible” decisions that “must be made methodically, carefully, slowly, with great deliberation and consultation.” Should we acquire our biggest rival? How much should we invest in an uncertain project? What is our return-to-office approach?

Significant research shows that a range of individual (e.g., narrative effect, uncertainty bias, loss aversion) and collective biases (e.g., planning fallacy, groupthink, hierarchy effect) inhibit the ability of organizations to handle decisions well. It is no surprise, then, that organizations will often bring in consultants to help with Type 1 challenges. At their best, the unbiased, outside view provided by consultants helps clients to make good decisions. At their worst, consultants add their own biases to the mix and/or succumb to political dynamics, making the decision-making process even worse.

Today, consultants have a new tool—generative AI (GenAI) using large language models (LLMs)—to help their clients make effective decisions. GenAI is an emergent technology, whose use has the potential to radically reshape the decision-support industry. This sprint course will be a hands-on laboratory that blends the best thinking about decision-making and experiential activities to give students a robust set of tools to use generative AI to help the organizations they advise to make good decisions.

AI-Driven Analytics and Society (Research-to-Practice Seminar)
James Siderius

The last decade has brought us tremendous advances in the power and sophistication of data- driven decision-making techniques at our disposal. Encouraged by this progress, we are witnessing a broad deployment of these techniques across the world. They now touch on and sometimes even govern just about every aspect of how businesses, and even people, operate on a day-to-day basis.

However, as much as these techniques were deployed with the promise of bringing a decisively positive change, it has become abundantly clear that they often are a mixed blessing, at best. Indeed, it turns out that the interface of algorithmic decision-making and society is rife with subtle and non-obvious interactions, undesirable feedback loops, and unintended consequences. How should we make sense of and navigate these issues?

The goal of this seminar is to survey some of the key challenges emerging in the context of the societal impact of data-driven decision making, as well as to create a forum where the students can discuss potential approaches to addressing these challenges. We will aim to discuss questions such as: How should businesses responsibility use, interpret, and make decisions from the output of machine learning models? How can we ensure big data sets are unbiased, fairly labeled, and being used responsibly by companies? What challenges will we face as businesses shift toward using generative AI and large language models for operations such as online customer service? Why does fake news spread faster than truthful news on online platforms like social media, and how do we combat it? Will automation replace unskilled labor, or simply make workers more productive?

Intense student involvement in both the presentation and the class discussion of the scientific papers is required. Like all RTP seminars, there will be a focus on using academic research to help you learn the analytical rigor to be an effective manager in an increasingly complex world.

Digital Duel: The US Versus the EU on Regulating Online Business (Sprint)
Andy Vorkink

This Tuck Sprint course will examine how the US and the EU have adopted and applied regulations on digital activities to companies operating across these huge markets and how businesses can comply with a rapidly changing business environment. This is a highly dynamic and shifting area whereby both the US and the EU are in effect playing regulatory catch-up to digital businesses which have expanded in recent years in what has largely been an unregulated environment. The course will examine the differences between US and EU policies and rules, what managers need to know about such differences and how management can comply with conflicting rules. Understanding the risks of non-compliance is critical for entities to safely operate internationally, for managers to make sound decisions and to avoid business altering decisions by government and judicial authorities.

A key objective of this course is to give students the skills and tools to analyze and create mechanisms to make business decisions which comply with laws and standards internationally and are consistent with local laws, such as by establishing compliance, safeguard and due diligence mechanisms to avoid sanctions and fines, as well as preventing reputational harm and political risk even if operating in compliance with national and international laws. Skills and knowledge acquired in the course will assist students to develop strategies for sustainable international business practices involving digital markets.

Equity Analytics in Organizations (Research-to-Practice Seminar)
Julia Melin

To have a competitive advantage in business, organizations need to leverage the full talents of an increasingly diverse population. Yet, many managers lack the analytical skills to identify whether their business practices create disparities in opportunity and/or outcomes for their workers. In this seminar, students will learn different ways to use data to identify and measure inequity in organizations that affect diversity goals, broadly defined, including but not limited to gender, race, social class, age, veteran status, parental status, and sexual orientation. Students will also learn methodological strategies for designing and testing solutions (e.g., longitudinal interventions, randomized field experiments) in real-world contexts (e.g., investment banking, high-tech, biotech, law firms). Course materials will include academic articles from management, sociology, social psychology, and economics to learn the analytical rigor required to make data-driven managerial decisions. The papers we read will leverage data to develop theory and offer empirical evidence to address questions such as:

By the end of this course, students will have learned analytical techniques to (a) identify inequity using data from various contexts (e.g., hiring evaluations, employee performance reviews, MBA starting salaries); (b) infer plausible causes of such inequities; and (c) design and test interventions to reduce observed inequities. Students will engage in active learning by co-leading class discussions of the papers each week and completing both a mid-term and final project that involve using real-world data to perform a detailed analysis of inequity.

FinTech (Regular Elective)
Juhani Linnainmaa

The purpose of this course is to provide an overview of various technological advances that have emerged in the financial services industry. We discuss technologies aimed at creating new and better ways of saving, borrowing, investing, and transacting. The specific technologies we focus relate to crypto (including blockchain, cryptocurrencies, and tokens), household lending market, real estate market, and robo-advising. We also give an overview of some machine learning techniques and principles as they relate to, e.g., the lending market and investment industry.

Human Behavior in Operations Management (Research-to-Practice Seminar)
Michelle Kinch

Operations management is an academic discipline that studies the design, management and improvement of the business processes governing both the transformation of raw materials into finished goods and services - and the delivery of those goods and services to customers. In OM, we aim for both efficiency (minimal waste of resources) and effectiveness (meeting customer requirements). Although people have always been a critical component of any operating system, historically, the field has focused on manufacturing environments. Like other traditionally quantitative, model-driven fields that have come to adopt behavioral perspectives, such as economics and finance, the study of behavioral operations has developed in the last 20 years.

Today, with the service sector accounting for 76% of GDP and 85% of employment, understanding the myriad ways that human behavior affects the efficiency and effectiveness of operating systems is more important than ever before. In this course, we will review papers that use experimental methods to investigate a topic in operations management. We will discuss the operational challenge, why understanding human behaviors are important to the efficiency or effectiveness goals, how the researchers approached the study and how business leaders might incorporate the research findings into managerial practice. In addition, students will have the opportunity to consider ways that they might design and test their own theories through experimentation in their own future managerial practice.

Introduction to B2B Marketing / Customer Growth Strategies and Tactics (Sprint)
Mark Hosbein T’90

Over three sessions the course will provide foundational knowledge of B2B marketing, both as a standalone practice and relative to consumer marketing. The material will be drawn from academics, thought leadership organizations, global consultancies, industry think tanks, and case studies. The course will provide the frameworks, tools and levers used by B2B marketers. We will bring all of that to life via case studies. And the instructor will draw on 25+ of B2B experience to support the insights and provide context.

The class is ideal for aspiring marketers as well as students who will go into finance, consulting or product leadership in an enterprise. Students planning on entering consumer marketing should know the basics (and differences) between consumer and enterprise marketing. The course will also serve the needs of future leaders in consulting, banking, private equity and technology by showcasing innovative growth strategies, internal team management and alignment, and M&A strategies to support growth. The ability to build and orchestrate customer driven growth is a core skill in all fields. Assignments will simulate real life issues and be based on actual tasks required in leadership roles.

Investing in Early-Stage Social Ventures (Practicum)
Curt Welling D’71, T’77 and Ramon Lecuona

This practicum provides students with technical and applied knowledge to assess the potential of early-stage ventures with social impact. More specifically, this practicum helps students:

Leading Diverse Organizations (Regular Elective)
Sonya Mishra

Using insights from cutting-edge behavioral and psychological research, this course provides students with skills to identify and address issues related to diversity, equity, and inclusion (DEI) within organizations. Students will develop an understanding of the barriers to DEI, such as systems of inequality, denial of privilege, biases that hinder support for DEI, and the many biases facing marginalized groups. Through lectures, in-class exercises, and case discussions, students will also learn about how organizational characteristics (e.g., power hierarchies, social networks, work culture) impact the efficacy of DEI interventions. Finally, students will learn how to improve organizational DEI at the individual level (e.g., addressing bias, allyship, empathetic leadership, psychological safety) and at the organizational level (e.g., hiring practices and workplace policies that measurably improve DEI). By the end of this course, students will be adept at identifying and addressing sources of inequity, having difficult conversations, mitigating problems associated with stereotypes, and managing diverse, equitable, and inclusive environments.

Marketing in Society (Research-to-Practice Seminar)
Nailya Ordabayeva

The public and media sometimes question the role of Marketing in society. Critics cite potential adverse implications of marketers’ actions for wellbeing. This research-to-practice seminar examines the impact of Marketing in society and the constructive role that Marketing and marketers can play in enhancing wellbeing outcomes and addressing societal challenges. We will delve into findings from cutting-edge academic research on the role of Marketing in society across a range of wellbeing domains (such as health, wealth, sustainability, diversity and representation, voice and activism). We will cover research papers that develop theory and present empirical tests of marketing’s impact on wellbeing outcomes in these domains. Building on the findings of these papers, we will discuss ideas for how research insights can be applied to enhance wellbeing outcomes and inclusivity in the marketplace and broader society. As in all Tuck RTP seminars, this course will focus and build on academic research to help you embrace the analytical rigor required to be an impactful manager (and a mindful consumer) in today’s complex marketplace. Consistent student engagement in the presentation and evaluation of the research ideas, methodologies, and implications will be required.

Moral Reasoning (Regular Elective)
Josh Lewis

How did President Harry Truman decide to use atomic weapons in 1945? How did Katherine Graham, Publisher of the Washington Post, consider the ethical dilemmas and business risks involved in publishing the Pentagon Papers and pursuing Watergate? Is Machiavelli’s treatise The Prince a pragmatic handbook every leader should read or a rationalization of thuggery?

Leaders regularly confront dilemmas with moral dimensions. They can arise urgently and unexpectedly, are generally complex, and can be career defining. This course in applied ethics is both abstract, in that it explores complex moral questions and the philosophical frameworks used to address them, and intensely practical, in that it deals with the types of moral challenges that business leaders face and introduces the tools required to lead an organization through them. Its ultimate objective is to enable students to better navigate the business world, and life as it is actually lived.

Course content includes renowned fiction, autobiography, moral philosophy, documentary film, and journalistic and historical narrative, with a diverse set of protagonists spanning centuries, cultures, and continents.

Professor Lewis notes: “Over a 30+ year career in venture capital and private equity I encountered any number of ethical dilemmas, several complex and relatively consequential. And although my training in moral philosophy was useful in equipping me with skills in abstract reasoning, I wish I’d taken a course in applied ethics like this one. Success in business requires a command of hard skills—strategy, finance, management, operations. That said, in retrospect, it was the difficult moral calls that I remember most clearly—and, regardless of how well or poorly I now believe I prosecuted those decisions, they were crucial turning points in my evolution as a professional.”

NLP, Machine Learning and AI in Finance (Research-to-Practice Seminar)
Gordon Phillips

We will study finance applications of new big data textual methods including Natural Language Processing (NLP)/ Machine Learning (ML), and Textual Artificial Intelligence (AI). We will examine how this broad area has applications in finance with tools that include simple text processing to more advanced tools such as machine learning and predictive AI. Areas that we will study that are using NLP include merger prediction and performance, profitability prediction, stock return prediction, evaluation of venture capital business plans, innovation and patenting, banking and other finance topics. Our study materials will be academic articles in finance and economics, not computer science. Students will be responsible for reading and presenting the materials in these articles as well as doing a final research project that would involve analysis of textual data using some of the methods covered in this course. There will be active learning in this course as students will help lead the discussion of various topic areas and we will have some Python exercises that have been developed with accompanying videos. Knowledge of Python is not required as we will guide students through some basic exercises in textual analysis applied to financial documents including 10Ks, earnings calls, and patent text.

Optimization Modeling for Prescriptive Analytics (Regular Elective)
James Siderius

This mini course expands on the core Analytics sequence through a deeper dive into the art of modeling, centered around essential tools in optimization. The goal of the course is to extend beyond predictive analytics and to develop richer prescriptive models for optimizing business operations in various marketplaces. We will focus on the modeling of prescriptive questions in a way that can be simply stated, solved efficiently, and whose insights can be communicated clearly.

Every class will be entirely “hands on” with an emphasis on active problem solving for more value-added learning. Each week will focus on a central topic in optimization, with the first session of each week centered around modeling techniques and the second session putting these skills into action with a data-driven case. Throughout the course we will focus on both classical management problems, such as production planning and commodity shipping, as well as modern operational problems, such as COVID-19 testing, cloud resource allocation, premium ride-hailing services, and personalized advertising through generative AI.

Topic wise, the course first provides an overview of the major types of linear programs, of the sort featured in the core, proceeding to more general models of strategic planning and control. Next, the course examines network models, including familiar problems such as optimal transportation routing (“special” network models) as well as general network-flow models. Then, we cover the formulation and solution of optimization models with logical constraints. We conclude by tackling non-linear models and analyzing algorithms for heuristic solutions to optimization models.

Personal Strategies for Achieving Wellbeing in Your Career (Sprint)
Grant Freeland

Much of your studies at Tuck are focused on content—strategy, operations, finance, people management, and more. And while these topics are critically important, a lot of your success in careers and life is actually driven by other things. Over the past decade or so, there has been an explosion in understanding these success factors and this Sprint is an MBA oriented version of a highly successful course being taught at the Harvard Kennedy School. The Sprint is structured into three themes: knowing yourself and what drives wellbeing (e.g., aspirations, motivations, values, purpose, happiness, grit, role of money); where are you going and how are you getting there (e.g., career satisfaction, career optionality, working across boundaries, networks, sponsorship); and building resilience (e.g., wellness, stress, mental health, work and family.) Because of the shortness of this Sprint, we mostly focus on the science and academics around these themes. Having said that, the course has a practical bent, and some self-reflection is required. Plus, students will be asked to experiment with some form of a wellbeing exercise.

Quantitative Investing with Python (Regular Elective)
Juhani Linnainmaa

The purpose of this course is to provide an introduction to quantitative investing using Python. Although no prior knowledge of Python is required, some familiarity (or comfort) with coding may be useful. We will work with Jupyter notebooks that you can run and edit. Even if you have never coded in Python, you can execute the code, see what happens, and modify the code to understand what the code does. The assignments are modifications and extensions of the code used in lectures, that is, they do not require you to code up from scratch anything you do not see in the classroom notebooks.

Quantitative investing in the context of this course means making systematic investment decisions informed by data. That is, there is little or no room for subjective judgments. We will introduce the basic Python libraries (e.g., NumPy, Pandas, scikit-learn, and stats models) that we need for acquiring and analyzing data and for completing financial computations such as creating trading strategies and evaluating returns. We start from constructing academic factors (such as value and momentum) and briefly discuss the principles of machine learning and the use (and the associated caveats) of ML techniques for predicting returns. The objective of the course is to give an overview of the methods used in quantitative investing.

Reverse Innovation (Sprint)
VG Govindarajan

Historically, corporations innovated in a rich country like the U.S. and sold those products in a poor country like India. Reverse Innovation is doing exactly the opposite. It is about innovating in a poor country like India and later selling those products in a rich country like the U.S.

This course is designed to ground students in the theory and practice of Reverse Innovation.

Startup Strategizing (Regular Elective)
Hart Posen

Entrepreneurship is economically vital and personally fulfilling—but success is elusive. Why? This course focuses on one explanation—success is not just the outcome of finding a great opportunity but also what you do with it. The startup’s strategy is the answer, as a growing research literature has documented. While developing a good business plan and pitch deck are important, as are practices such as experimentation and pivoting, they complement, not substitute, a well-founded strategy. Startup Strategizing will help you develop superior strategies for the ventures you found or join, and evaluate the strategies of startups you might invest in. Building on your work in the Strategy core course and complementing related electives (e.g., Ecosystems Design, Design Thinking, Social Enterprise, Entrepreneurial Thinking), we will develop a deep understanding of the core strategic choices facing entrepreneurs and a conceptual framework for how to address them.

Women, Gender and Leadership in the New Workplace (Regular Elective)
Stacy Blake-Beard

Over the past decades, women have steadily moved into higher levels of management and leadership where they now occupy key positions in the public and private sectors and have established themselves as a force in most workplaces. However, there are still challenges that they are facing. The work place experiences of women are informed by societal expectations that are deeply ingrained in how we show up—gender norms. In this course, we will focus on how gender norms have impacted women’s careers, as well as the ways that gender norms affect work, leadership, and professional success in general. We will delve into issues that are commonly included in discussions on women, gender, and leadership (i.e. work-life balance, networking, and bias). We will expand to more recent dimensions of the new workplace (i.e. the influence of technology, the different career experiences of women across the globe). Through the course, we will have a forum to identify, at interpersonal and organizational levels, the challenges that women have faced—and the strategies they have utilized—on their career path. We will also diagnose gender and power dynamics in the workplace and evaluate alterative reactions/responses to enhance individual and group effectiveness. With each of the topics, you will be encouraged to think of your role as leaders and how you can use those competencies to create and/or contribute to workplaces that are sensitive to the importance of gender equity.