Bizcast: Walmart’s Chief People Officer Donna Morris on the Future of Work
In this episode, Morris joins CBS Professor Stephan Meier to discuss how Walmart is building a resilient, tech-powered, and people-led workplace.
Through cutting-edge curricular innovation, our MBA, Executive MBA, MS, and PhD programs introduce new courses and research that seamlessly integrate AI into the student experience. From exploring the impact of AI across industries to developing hands-on experience with the latest tools, students can build confidence in using the latest tech in their chosen fields.
AI plays a critical role in the rapidly evolving modern workplace, and with a curriculum that emphasizes its societal and business implications, students can fully prepare to lead in this rapidly evolving landscape. Explore how our students, faculty, centers and programs are engaging with AI at Columbia Business School.
In this episode, Morris joins CBS Professor Stephan Meier to discuss how Walmart is building a resilient, tech-powered, and people-led workplace.
Research from Columbia Business School examines the challenges posed by generative AI in hiring and entrepreneurial pitching, offering insights into when AI helps — and when it hinders.
Chris Levesque, President and CEO of TerraPower, explains how next-generation reactors and innovative energy storage are reshaping nuclear energy's role in the global transition to sustainability.
Award-winning research from Professor Laura Doval tackles the “limited commitment” problem in economics, offering a model that helps governments and firms adjust rules and strategies based on new information over time.
Columbia Business School Professor Stephan Meier explains how leaders can calm AI-related concerns, while also creating value.
Columbia Business School Professor Olivier Toubia shares the many upsides – and downsides – of AI in the workplace.
Ashli Carter, a lecturer at Columbia Business School, explains one of the ways she uses AI to help students build resilience.
Columbia Business School Professor Omar Besbes explains how AI is democratizing workplace productivity.
AI is integrated into our courses in ways that support student’s projects and inspire rich class discussions. Tools like ChatGPT are used to assist in breaking down complex research techniques, run business simulations, visualize data in real time, and to show students to think in new ways and explore innovative solutions.
At Columbia Business School, we introduce you to the methods and tools that organizations around the world use to leverage data and artificial intelligence. You will learn how these techniques work, and how to use them. The curriculum spans everything from basic data analysis to generative AI, and contains classes suitable for all skill levels.
Generative artificial intelligence (AI) is reshaping industries worldwide, and higher education is no exception. Much like other transformative innovations before it, AI-powered language models have introduced new opportunities and challenges, changing the way students learn and how instructors teach.
At Columbia Business School, the Arthur J. Samberg Institute for Teaching Excellence serves as a guiding force in this ongoing transformation, equipping faculty with the knowledge, tools, and strategies they need to leverage generative AI for effective teaching.
The Digital Future Initiative focuses Columbia Business School’s world-class research and teaching on how technology is altering all industries and the fabric of daily life.
AI is changing the way we work, and the Career Management Center (Careers) at Columbia Business School has organized numerous AI-focused events and introduced AI-powered tools to help students and alumni adapt to these changes and achieve their long-term professional goals.
More upcoming AI events will be added soon.
The rise of low-cost artificial intelligence (AI) technologies offers significant potential for businesses globally, yet AI adoption remains uneven. What shapes this unequal adoption? While prior work attributes adoption patterns to demand-side factors including physical costs and complementary assets, we theorize that AI entrepreneurs' strategic choice to target specific markets creates both search and perceived-fit frictions for firms outside of those markets.
Language plays a crucial role in marketing, influencing outcomes such as consumer engagement and decision-making. Although prior research has extensively analyzed the relationship between linguistic features and business outcomes, most approaches have been descriptive or predictive, limiting their value for crafting more effective content. Understanding the causal effects of specific linguistic features is essential but challenging because, in real-world settings, the focal textual feature often changes simultaneously with other confounding factors.
Geoeconomic pressure—the use of existing economic relationships by governments to achieve geopolitical or economic ends—has become a prominent feature of global power dynamics. This paper introduces a methodology using large language models (LLMs) to systematically extract signals of geoeconomic pressure from large textual corpora. We quantify not just the direct effects of implemented policies but also the off-path threats that induce compliance without formal action. We systematically identify governments, firms, tools, and activities that are involved in this pressure.
How has Wikipedia activity changed for articles with content similar to ChatGPT following its introduction? We estimate the impact using differences-in-differences models, with dissimilar Wikipedia articles as a baseline for comparison, to examine how changes in voluntary knowledge contributions and information-seeking behavior differ by article content. Our analysis reveals that newly created, popular articles whose content overlaps with ChatGPT 3.5 saw a greater decline in editing and viewership after the November 2022 launch of ChatGPT than dissimilar articles did.
In this letter, we summarize our recent work on the welfare impact of recommendation algorithms and propose questions for further study. We model recommendation algorithms as an information structure, which shapes how a third party takes actions that affect the welfare of different individuals in a population. Each recommendation algorithm thus induces a welfare profile, describing the expected payoffs of different individuals when the third party takes actions following the algorithm.
We aim to stimulate discussion on how innovation research within marketing can use a better world (BW) perspective to help innovation become a driver of positive change in the world. In this "Challenging the Boundaries" series paper, we hope to provide purposeful research opportunities for scholars seeking to bridge innovation research with the BW movement. We frame our discussion with four areas of innovation research in marketing that are particularly relevant to BW objectives.
Our educational model is predicated on an expert lecturing to a class of attentive disciples. We rely on standardized repeated exams. As a junior accounting professor, I was encouraged to take a senior faculty member’s teaching notes and simply go and deliver the material. Rely on older exams or some variant thereof. Have a standard key to grade the exams. In essence, minimize the time spent on teaching so that I can work on research and get tenure. To be fair, my senior professors were watching out for me and were trying to put me on the shortest path to tenure.
Research by Columbia's Elizabeth Friedman reveals Airbnb hosts who smile in profile photos receive 3.5% more bookings, with male hosts seeing an 8.7% increase. The Wall Street Journal explores how smiling signals trustworthiness, especially benefiting inexperienced hosts and those in high-crime areas.
We work with organizations to shape the “future of work” while overcoming common barriers to change implementation. As organizations set out major transformations, we both encourage and caution.