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(1,089)
- Faculty Publications (429)
- 2024
- Working Paper
Climate Solutions, Transition Risk, and Stock Returns
By: Shirley Lu, Edward J. Riedl, Simon Xu and George Serafeim
Using large language models to measure firms' climate solution products and services, we find that high-climate solution firms exhibit lower stock returns and higher market valuation multiples. Their stock prices respond positively to events signaling increased demand... View Details
Keywords: Technology; Generative Ai; Large Language Models; Climate Finance; Climate Change; Innovation and Invention; Environmental Sustainability; AI and Machine Learning; Investment; Financial Markets
Lu, Shirley, Edward J. Riedl, Simon Xu, and George Serafeim. "Climate Solutions, Transition Risk, and Stock Returns." Harvard Business School Working Paper, No. 25-024, November 2024.
- November–December 2024
- Article
Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing
By: Kirk Bansak and Elisabeth Paulson
This study proposes two new dynamic assignment algorithms to match refugees and asylum seekers to geographic localities within a host country. The first, currently implemented in a multi-year pilot in Switzerland, seeks to maximize the average predicted employment... View Details
Bansak, Kirk, and Elisabeth Paulson. "Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing." Operations Research 72, no. 6 (November–December 2024): 2375–2390.
- 2025
- Working Paper
Generative AI and the Nature of Work
By: Manuel Hoffmann, Sam Boysel, Frank Nagle, Sida Peng and Kevin Xu
Recent advances in artificial intelligence (AI) technology demonstrate a considerable potential
to complement human capital intensive activities. While an emerging literature documents wide-ranging
productivity effects of AI, relatively little attention has been paid... View Details
Keywords: Generative Ai; Digital Work; Open Source Software; Knowledge Economy; AI and Machine Learning; Open Source Distribution; Organizational Structure; Performance Productivity; Labor
Hoffmann, Manuel, Sam Boysel, Frank Nagle, Sida Peng, and Kevin Xu. "Generative AI and the Nature of Work." Harvard Business School Working Paper, No. 25-021, October 2024. (Revised April 2025.)
- October 2024 (Revised April 2025)
- Case
Nvidia
By: Andy Wu and Matt Higgins
This case study examines Nvidia's strategic pivot from gaming GPUs to becoming a leader in general-purpose computing and AI. It explores how Nvidia leveraged its GPU architecture to dominate the growing fields of data center acceleration and AI training, outpacing... View Details
- October 2024
- Technical Note
Prompt Engineering
By: Michael Parzen and Jo Ellery
This note covers the basics of prompt engineering, a key tool for making use of modern generative AI. We discuss the principles of prompt engineering and illustrate these principles with techniques for asking questions. We further list the types of prompts that can be... View Details
Parzen, Michael, and Jo Ellery. "Prompt Engineering." Harvard Business School Technical Note 625-056, October 2024.
- October 2024
- Case
Reed Group and Succession in a Family Business: An Impossible Job to Fill?
By: Lauren H. Cohen and Tonia Labruyere
James Reed had taken over Reed Group, the recruitment and career services company his father had founded and built, in 1994. He was now reflecting on succession planning and other challenges that lay ahead: with no obvious choice among his family members, he needed to... View Details
Keywords: Charity; Succession Planning; Family Business; Values and Beliefs; Management Succession; Mission and Purpose; Family Ownership; Philanthropy and Charitable Giving; Family and Family Relationships; Recruitment; AI and Machine Learning; Employment Industry; United Kingdom; London
Cohen, Lauren H., and Tonia Labruyere. "Reed Group and Succession in a Family Business: An Impossible Job to Fill?" Harvard Business School Case 825-084, October 2024.
- October 2024 (Revised February 2025)
- Case
AI and Brand Management: Promises and Perils
By: Julian De Freitas and Elie Ofek
As AI gains traction across industries, companies anticipate that AI will revolutionize both backend processes and customer-facing interactions—with brands eager to leverage AI for tailored marketing materials and automated consumer engagements. Yet, despite a dramatic... View Details
Keywords: AI and Machine Learning; Brands and Branding; Reputation; Technology Adoption; Competitive Advantage
De Freitas, Julian, and Elie Ofek. "AI and Brand Management: Promises and Perils." Harvard Business School Case 525-021, October 2024. (Revised February 2025.)
- 2025
- Working Paper
Lessons from an App Update at Replika AI: Identity Discontinuity in Human-AI Relationships
By: Julian De Freitas, Noah Castelo, Ahmet Kaan Uğuralp and Zeliha Oğuz-Uğuralp
As consumers increasingly interact with AI applications specialized for social relationships, what
is the nature and depth of these relationships among actual users, and can company actions
influence these dynamics? We find that active users of the US-based AI... View Details
De Freitas, Julian, Noah Castelo, Ahmet Kaan Uğuralp, and Zeliha Oğuz-Uğuralp. "Lessons from an App Update at Replika AI: Identity Discontinuity in Human-AI Relationships." Harvard Business School Working Paper, No. 25-018, October 2024. (Revised May 2025.)
- 2025
- Working Paper
Global Evidence on Gender Gaps and Generative AI
By: Nicholas G. Otis, Solène Delecourt, Katelynn Cranney and Rembrand Koning
Generative AI has the potential to transform productivity and reduce inequality, but only if adopted broadly. In this paper, we show that recently identified gender gaps in generative AI use are nearly universal. Synthesizing data from 18 studies covering more than... View Details
Otis, Nicholas G., Solène Delecourt, Katelynn Cranney, and Rembrand Koning. "Global Evidence on Gender Gaps and Generative AI." Harvard Business School Working Paper, No. 25-023, October 2024. (Revised January 2025.)
- September–October 2024
- Article
The Crowdless Future? Generative AI and Creative Problem-Solving
The rapid advances in generative artificial intelligence (AI) open up attractive opportunities for creative problem-solving through human-guided AI partnerships. To explore this potential, we initiated a crowdsourcing challenge focused on sustainable, circular economy... View Details
Keywords: Large Language Models; Generative Ai; Crowdsourcing; AI and Machine Learning; Creativity; Technological Innovation
Boussioux, Léonard, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim R. Lakhani. "The Crowdless Future? Generative AI and Creative Problem-Solving." Organization Science 35, no. 5 (September–October 2024): 1589–1607.
- September 2024
- Background Note
Copyright and Fair Use
By: David B. Yoffie
The U.S. Copyright Office defines a copyright as “a type of intellectual property that protects original works of authorship as soon as an author fixes the work in a tangible form of expression.” Two core principles of copyright are originality and fixation. A work is... View Details
Yoffie, David B. "Copyright and Fair Use." Harvard Business School Background Note 725-394, September 2024.
- September 2024
- Exercise
Finding Your 'Jagged Frontier': A Generative AI Exercise
By: Mitchell Weiss
In 2023 a set of scholars set out to study the effect of artificial intelligence (AI) on the quality and productivity of knowledge workers—in this specific instance, management consultants. They wanted to know across a range of tasks in a workflow, which, if any, would... View Details
Keywords: AI and Machine Learning; Performance Productivity; Performance Evaluation; Consulting Industry
Weiss, Mitchell. "Finding Your 'Jagged Frontier': A Generative AI Exercise." Harvard Business School Exercise 825-070, September 2024.
- 2024
- Working Paper
Igniting Innovation: Evidence from PyTorch on Technology Control in Open Collaboration
By: Daniel Yue and Frank Nagle
Many companies offer free access to their technology to encourage outside addon
innovation, hoping to later profit by raising prices or harnessing the power of the crowd
while continuing to steer the direction of innovation. They can achieve this balance by
opening... View Details
Keywords: Technological Innovation; Power and Influence; Collaborative Innovation and Invention; Corporate Governance
Yue, Daniel, and Frank Nagle. "Igniting Innovation: Evidence from PyTorch on Technology Control in Open Collaboration." Harvard Business School Working Paper, No. 25-013, September 2024.
- September 23, 2024
- Article
AI Wants to Make You Less Lonely. Does It Work?
De Freitas, Julian. "AI Wants to Make You Less Lonely. Does It Work?" Wall Street Journal (September 23, 2024), R.11.
- 2024
- Working Paper
Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python
By: Melissa Ouellet and Michael W. Toffel
This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in... View Details
Keywords: Empirical Methods; Empirical Operations; Statistical Methods And Machine Learning; Statistical Interferences; Research Analysts; Analytics and Data Science; Mathematical Methods
Ouellet, Melissa, and Michael W. Toffel. "Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python." Harvard Business School Working Paper, No. 25-010, August 2024.
- September 2024 (Revised January 2025)
- Exercise
Building an AI First Snack Company: A Hands-on Generative AI Exercise
By: Iavor I. Bojinov
Although the term 'Generative AI' (GenAI) is widely recognized, its practical application in daily workflows has yet to be understood. This exercise introduces students to GenAI tools, demonstrating how they can be seamlessly integrated into professional work practices... View Details
Keywords: AI and Machine Learning; Technology Adoption; Marketing Strategy; Product Launch; Brands and Branding
Bojinov, Iavor I. "Building an AI First Snack Company: A Hands-on Generative AI Exercise." Harvard Business School Exercise 625-052, September 2024. (Revised January 2025.)
- September–October 2024
- Article
How AI Can Power Brand Management
By: Julian De Freitas and Elie Ofek
Marketers have begun experimenting with AI to improve their brand-management efforts. But unlike other marketing tasks, brand management involves more than just repeatedly executing one specialized function. Long considered the exclusive domain of creative talent, it... View Details
Keywords: Creativity; AI and Machine Learning; Brands and Branding; Product Positioning; Customer Focus and Relationships
De Freitas, Julian, and Elie Ofek. "How AI Can Power Brand Management." Harvard Business Review 102, no. 5 (September–October 2024): 108–114.
- 2024
- Article
Learning Under Random Distributional Shifts
By: Kirk Bansak, Elisabeth Paulson and Dominik Rothenhäusler
Algorithmic assignment of refugees and asylum seekers to locations within host
countries has gained attention in recent years, with implementations in the U.S.
and Switzerland. These approaches use data on past arrivals to generate machine
learning models that can... View Details
Bansak, Kirk, Elisabeth Paulson, and Dominik Rothenhäusler. "Learning Under Random Distributional Shifts." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 27th (2024).
- 2024
- Working Paper
The Wade Test: Generative AI and CEO Communication
By: Prithwiraj Choudhury, Bart S. Vanneste and Amirhossein Zohrehvand
Can generative artificial intelligence (Gen-AI) transform the role of the CEO? This study investigates
whether Gen-AI can mimic a human CEO and whether employees display aversion to Gen-AI
communication. We present a framework of Gen-AI aversion that distinguishes... View Details
Choudhury, Prithwiraj, Bart S. Vanneste, and Amirhossein Zohrehvand. "The Wade Test: Generative AI and CEO Communication." Harvard Business School Working Paper, No. 25-008, August 2024. (Revised May 2025.)
- August 2024 (Revised March 2025)
- Case
DBS' AI Journey
By: Feng Zhu, Harold Zhu and Adina Wong
Headquartered in Singapore, DBS Bank, one of Asia's leading financial services groups, embarked on a multi-year digital transformation under CEO Piyush Gupta in 2014. It was then that DBS also began experimenting with AI to drive value for the business and customers.... View Details
Keywords: Corporate Governance; AI and Machine Learning; Digital Transformation; Risk Management; Value Creation; Banking Industry; Financial Services Industry; Asia; Singapore
Zhu, Feng, Harold Zhu, and Adina Wong. "DBS' AI Journey." Harvard Business School Case 625-053, August 2024. (Revised March 2025.)