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Show Results For
- All HBS Web
(1,031)
- People (1)
- News (187)
- Research (621)
- Events (11)
- Multimedia (3)
- Faculty Publications (502)
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- April 1, 2024
- Other Article
Paying For AI In Healthcare: Setting The Right Precedent Amidst Growing Use
By: Mitchell Tang, Kaylee Wilson and Ateev Mehrotra
Tang, Mitchell, Kaylee Wilson, and Ateev Mehrotra. "Paying For AI In Healthcare: Setting The Right Precedent Amidst Growing Use." Health Affairs Forefront (April 1, 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.
- July 2024 (Revised December 2024)
- Case
Compass Ethics: Governing Through Ethical Principles at WeCorp Industries
By: Elisabeth Kempf and Jesse M. Shapiro
Andrew Hill is Chief Information Officer at WeCorp, a UK-based defense technology startup specializing in drone technology. WeCorp faces decisions about international licensing and AI integration in its drones. In partnership with Compass Ethics, Hill aims to establish... View Details
Keywords: Business Startups; Decision Making; Ethics; Entrepreneurial Finance; AI and Machine Learning; Technology Industry; United Kingdom
Kempf, Elisabeth, and Jesse M. Shapiro. "Compass Ethics: Governing Through Ethical Principles at WeCorp Industries." Harvard Business School Case 224-105, July 2024. (Revised December 2024.)
- Forthcoming
- Article
Engaging Customers with AI in Online Chats: Evidence from a Randomized Field Experiment
By: Shunyuan Zhang and Das Narayandas
We examine how artificial intelligence (AI) affected the productivity of customer service agents and customer sentiment in online interactions. Collaborating with a meal delivery company, we conducted a randomized field experiment that exploited exogenous variation in... View Details
- August 13, 2024
- Editorial
Can AI Save Physicians from Burnout?
By: Susanna Gallani, Lidia Moura and Katie Sonnefeldt
Gallani, Susanna, Lidia Moura, and Katie Sonnefeldt. "Can AI Save Physicians from Burnout?" Harvard Business School Working Knowledge (August 13, 2024).
- March 2024
- Simulation
'Storrowed'
By: Mitchell Weiss
The game was built to accompany "Storrowed": A Generative AI Exercise, available through Harvard Business Publishing. The game adds a timing element to "Storrowed" and enables the teacher to reward teams for strong prompts or penalize teams for believing AI... View Details
- April 2021
- Case
Distinct Software
By: Das Narayandas, Arijit Sengupta and Jonathan Wray
Distinct Software (disguised name), a global enterprise software company, is at an important point in its growth trajectory where the luster of its mantra of “grow and win at any cost” has dimmed with increasing competition and margin pressures. To help navigate its... View Details
Keywords: Artificial Intelligence; Marketing; Sales; Performance Productivity; Technological Innovation; AI and Machine Learning
Narayandas, Das, Arijit Sengupta, and Jonathan Wray. "Distinct Software." Harvard Business School Case 521-101, April 2021.
- March 2019
- Teaching Note
Numenta: Inventing and (or) Commercializing AI
By: David B. Yoffie
This teaching notes accompanies the Numenta case, HBS No. 716-469. The focus is how to scale a new artificial intelligence technology, how to build a platform and overcome chicken-or-the-egg problems, and how to utilize open source software and licensing. View Details
- August 2024
- 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.
- 2024
- Working Paper
Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions
By: Caleb Kwon, Ananth Raman and Jorge Tamayo
We investigate whether corporate officers should grant managers discretion to override AI-driven demand forecasts and labor scheduling tools. Analyzing five years of administrative data from a large grocery retailer using such an AI tool, encompassing over 500 stores,... View Details
Keywords: AI and Machine Learning; Forecasting and Prediction; Working Conditions; Performance Productivity
Kwon, Caleb, Ananth Raman, and Jorge Tamayo. "Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions." Working Paper, April 2024.
- 2024
- Working Paper
Old Moats for New Models: Openness, Control, and Competition in Generative AI
By: Pierre Azoulay, Joshua L. Krieger and Abhishek Nagaraj
Drawing insights from the field of innovation economics, we discuss the likely competitive environment shaping generative AI advances. Central to our analysis are the concepts of appropriability—whether firms in the industry are able to control the knowledge generated... View Details
Azoulay, Pierre, Joshua L. Krieger, and Abhishek Nagaraj. "Old Moats for New Models: Openness, Control, and Competition in Generative AI." NBER Working Paper Series, No. 7442, May 2024.
- July 2024
- Article
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety... View Details
Keywords: Autonomy; Chatbots; New Technology; Brand Crises; Mental Health; Large Language Model; AI and Machine Learning; Behavior; Well-being; Technological Innovation; Ethics
De Freitas, Julian, Ahmet Kaan Uğuralp, Zeliha Uğuralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Journal of Consumer Psychology 34, no. 3 (July 2024): 481–491.
- September 2023
- Case
Ada: Cultivating Investors
By: Reza Satchu and Patrick Sanguineti
Mike Murchison, co-founder and CEO of Ada, has an enviable dilemma. Launched in 2016 by Murchison and his co-founder David Hariri, Ada is an AI-native company that aims to revolutionize how businesses approach customer service. The company has already attracted a buzz,... View Details
Keywords: Founder; Fundraising; Business Startups; Decisions; Entrepreneurship; Venture Capital; AI and Machine Learning; Technology Industry
Satchu, Reza, and Patrick Sanguineti. "Ada: Cultivating Investors." Harvard Business School Case 824-090, September 2023.
- 2024
- Working Paper
The Financial Anatomy of Climate Solutions: A Large Language Model Approach to Company Classification and Analysis
By: Shirley Lu and George Serafeim
Leveraging advancements in large language models (LLM), we study the financial characteristics of firms offering climate solutions-products and services aimed at fostering a transition to a low-carbon economy. We use a new measure that applies LLM to 10-K Item 1... View Details
Keywords: Climate; Climate Finance; Innovation; Technology; Financial Statement Analysis; AI and Machine Learning; Climate Change; Environmental Sustainability; Analysis; Financial Statements
Lu, Shirley, and George Serafeim. "The Financial Anatomy of Climate Solutions: A Large Language Model Approach to Company Classification and Analysis." Harvard Business School Working Paper, No. 25-026, August 2024.
- 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.)
- Forthcoming
- Article
Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation
By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
Even if algorithms make better predictions than humans on average, humans may sometimes have private information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by... View Details
Keywords: AI and Machine Learning; Analytics and Data Science; Forecasting and Prediction; Digital Marketing
Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation." Management Science (forthcoming).
- July–August 2024
- Article
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to... View Details
Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.
- June 2017
- Teaching Note
IBM Transforming, 2012–2016: Ginni Rometty Steers Watson
By: Rosabeth Moss Kanter and Jonathan Cohen
Ginni Rometty, who became IBM CEO in 2012, led efforts to transform the company around cognitive computing and the AI platform Watson. This Teaching Note helps instructors understand and teach the Harvard Business School case “IBM Transforming, 2012–2016: Ginni Rometty... View Details
- May 2024
- Article
The Health Risks of Generative AI-Based Wellness Apps
By: Julian De Freitas and G. Cohen
Artifcial intelligence (AI)-enabled chatbots are increasingly being used to
help people manage their mental health. Chatbots for mental health and
particularly ‘wellness’ applications currently exist in a regulatory ‘gray area’.
Indeed, most generative AI-powered... View Details
Keywords: AI and Machine Learning; Well-being; Governing Rules, Regulations, and Reforms; Applications and Software
De Freitas, Julian, and G. Cohen. "The Health Risks of Generative AI-Based Wellness Apps." Nature Medicine 30, no. 5 (May 2024): 1269–1275.
- March 2022
- Article
Winner Takes All? Tech Clusters, Population Centers, and the Spatial Transformation of U.S. Invention
By: Brad Chattergoon and William R. Kerr
U.S. invention has become increasingly concentrated around major tech centers since the 1970s, with implications for how much cities across the country share in concomitant local benefits. Is invention becoming a winner-takes-all race? We explore the rising spatial... View Details
Keywords: Clusters; Invention; Agglomeration; Artificial Intelligence; Innovation and Invention; Patents; Applications and Software; Industry Clusters; AI and Machine Learning
Chattergoon, Brad, and William R. Kerr. "Winner Takes All? Tech Clusters, Population Centers, and the Spatial Transformation of U.S. Invention." Art. 104418. Research Policy 51, no. 2 (March 2022).