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Show Results For
- All HBS Web
(2,852)
- People (14)
- News (652)
- Research (1,576)
- Events (19)
- Multimedia (9)
- Faculty Publications (845)
- 16 Nov 2020
- Blog Post
Flatiron School: Reflections from Summer 2020
to provide visualization of data, machine learning models for prediction, and most importantly, insights that could influence the company’s strategy. To this end, the knowledge... View Details
Keywords: All Industries
- Student-Profile
Ta-Wei "David" Huang
management and using causal inference / machine learning tools to solve marketing problems.” It was this motivation that led him to pursue a Ph.D. Initially, David’s familiarity with HBS was limited to the... View Details
- October 31, 2022
- Article
Achieving Individual—and Organizational—Value with AI
By: Sam Ransbotham, David Kiron, François Candelon, Shervin Khodabandeh and Michael Chu
New research shows that employees derive individual value from AI when using the technology improves their sense of competency, autonomy, and relatedness. Likewise, organizations are far more likely to obtain value from AI when their workers do. This report offers key... View Details
Ransbotham, Sam, David Kiron, François Candelon, Shervin Khodabandeh, and Michael Chu. "Achieving Individual—and Organizational—Value with AI." MIT Sloan Management Review, Big Ideas Artificial Intelligence and Business Strategy Initiative (website) (October 31, 2022). (Findings from the 2022 Artificial Intelligence and Business Strategy Global Executive Study and Research Project.)
- July 2024
- Article
AI, ROI, and Sales Productivity
Artificial intelligence (AI) is now a loose term for many different things and at the peak of its hype curve. So managers hitch-their-pitch to the term in arguing for resources. But like any technology, its business value depends upon actionable use cases embraced by... View Details
Cespedes, Frank V. "AI, ROI, and Sales Productivity." Top Sales Magazine (July 2024), 12–13.
- March 16, 2021
- Article
From Driverless Dilemmas to More Practical Commonsense Tests for Automated Vehicles
By: Julian De Freitas, Andrea Censi, Bryant Walker Smith, Luigi Di Lillo, Sam E. Anthony and Emilio Frazzoli
For the first time in history, automated vehicles (AVs) are being deployed in populated environments. This unprecedented transformation of our everyday lives demands a significant undertaking: endowing
complex autonomous systems with ethically acceptable behavior. We... View Details
Keywords: Automated Driving; Public Health; Artificial Intelligence; Transportation; Health; Ethics; Policy; AI and Machine Learning
De Freitas, Julian, Andrea Censi, Bryant Walker Smith, Luigi Di Lillo, Sam E. Anthony, and Emilio Frazzoli. "From Driverless Dilemmas to More Practical Commonsense Tests for Automated Vehicles." Proceedings of the National Academy of Sciences 118, no. 11 (March 16, 2021).
- 2024
- Case
EPCorp: Convincing the C-Suite
By: Jacob M. Cook
In EPCorp: Convincing the C-Suite, Shivani Bahl is attempting to sell EPCorp's CEO, Debbie Sullivan, on her ideas for not only a new website upgrade but also a more expansive vision on how data and Generative AI can be used to grow the company. Debbie is understandably... View Details
Cook, Jacob M. "EPCorp: Convincing the C-Suite." Harvard Business Publishing Case, 2024. (Quick Case.)
- August 25, 2022
- Article
Find the Right Pace for Your AI Rollout
By: Rebecca Karp and Aticus Peterson
Implementing AI can introduce disruptive change and disfranchise staff and employees. When members are reluctant to adopt a new technology, they might hesitate to use it, push back against its deployment, or use it in limited capacity — which affects the benefits an... View Details
Karp, Rebecca, and Aticus Peterson. "Find the Right Pace for Your AI Rollout." Harvard Business Review Digital Articles (August 25, 2022).
- Article
Fake AI People Won't Fix Online Dating
Computer-generated images may inspire even more distrust and surely won’t lead to the love of a lifetime. View Details
Keywords: Artificial Intelligence; Dating Services; Internet and the Web; Ethics; AI and Machine Learning
Kominers, Scott Duke. "Fake AI People Won't Fix Online Dating." Bloomberg Opinion (January 16, 2020).
- July–August 2021
- Article
Why You Aren't Getting More from Your Marketing AI
By: Eva Ascarza, Michael Ross and Bruce G.S. Hardie
Fewer than 40% of companies that invest in AI see gains from it, usually because of one or more of these errors: (1) They don’t ask the right question, and end up directing AI to solve the wrong problem. (2) They don’t recognize the differences between the value of... View Details
Keywords: Artificial Intelligence; Marketing; Decision Making; Communication; Framework; AI and Machine Learning
Ascarza, Eva, Michael Ross, and Bruce G.S. Hardie. "Why You Aren't Getting More from Your Marketing AI." Harvard Business Review 99, no. 4 (July–August 2021): 48–54.
- July 2024
- Case
Replika AI: Alleviating Loneliness (A)
By: Shikhar Ghosh and Shweta Bagai
Eugenia Kuyda launched Replika AI in 2017 as an empathetic digital companion to combat loneliness and provide emotional support. The platform surged in popularity during the COVID-19 pandemic, offering non-judgmental support to isolated users. By 2023, Replika boasted... View Details
Keywords: Entrepreneurship; Ethics; Health Pandemics; AI and Machine Learning; Well-being; Technology Industry
Ghosh, Shikhar, and Shweta Bagai. "Replika AI: Alleviating Loneliness (A)." Harvard Business School Case 824-088, July 2024.
- 13 Aug 2018
- Blog Post
Following My Dream: Launching a Venture
smoodi during my second year at HBS. During fall, our goal will be to raise funds and build a first machine prototype allowing for further testing. Several companies have already signed up for our beta-test. Having the best View Details
Keywords: Entrepreneurship
- 2025
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers
By: Matthew DosSantos DiSorbo, Kris Ferreira, Maya Balakrishnan and Jordan Tong
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). How can humans and algorithms work together to make... View Details
DosSantos DiSorbo, Matthew, Kris Ferreira, Maya Balakrishnan, and Jordan Tong. "Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers." Working Paper, May 2025.
- 2023
- Article
Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators
By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details
Jakubowski, Benjamin, Siram Somanchi, Edward McFowland III, and Daniel B. Neill. "Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators." Journal of Machine Learning Research 24, no. 133 (2023): 1–57.
- May 2022
- Supplement
Borusan CAT: Monetizing Prediction in the Age of AI (B)
By: Navid Mojir and Gamze Yucaoglu
Borusan Cat is an international distributor of Caterpillar heavy machines. In 2021, it had been three years since Ozgur Gunaydin (CEO) and Esra Durgun (Director of Strategy, Digitization, and Innovation) started working on Muneccim, the company’s predictive AI tool.... View Details
Keywords: AI and Machine Learning; Commercialization; Technology Adoption; Industrial Products Industry; Turkey; Middle East
Mojir, Navid, and Gamze Yucaoglu. "Borusan CAT: Monetizing Prediction in the Age of AI (B)." Harvard Business School Supplement 522-045, May 2022.
- 02 Oct 2018
- First Look
New Research and Ideas, October 2, 2018
presents researchers with the possibility of using large and new datasets related to text and image repositories. In this paper, we make a methodological contribution to strategy research by documenting a novel synthesis of two machine... View Details
Keywords: Dina Gerdeman
- 2024
- Working Paper
Displacement or Complementarity? The Labor Market Impact of Generative AI
By: Wilbur Xinyuan Chen, Suraj Srinivasan and Saleh Zakerinia
Generative AI is poised to reshape the labor market, affecting cognitive and white-collar occupations in ways distinct from past technological revolutions. This study examines whether generative AI displaces workers or augments their jobs by analyzing labor demand and... View Details
Keywords: Generative Ai; Labor Market; Automation And Augmentation; Labor; AI and Machine Learning; Competency and Skills
Chen, Wilbur Xinyuan, Suraj Srinivasan, and Saleh Zakerinia. "Displacement or Complementarity? The Labor Market Impact of Generative AI." Harvard Business School Working Paper, No. 25-039, December 2024.
- December 2024 (Revised January 2025)
- Technical Note
A Guide to the Vocabulary, Evolution, and Impact of Artificial Intelligence (AI)
By: Shane Greenstein, Nathaniel Lovin, Scott Wallsten, Kerry Herman and Susan Pinckney
A note on the vocabulary, evolution, and impact of AI. View Details
Keywords: Artificial Intelligence; Software; AI and Machine Learning; Technology Adoption; Technological Innovation; Technology Industry
Greenstein, Shane, Nathaniel Lovin, Scott Wallsten, Kerry Herman, and Susan Pinckney. "A Guide to the Vocabulary, Evolution, and Impact of Artificial Intelligence (AI)." Harvard Business School Technical Note 625-039, December 2024. (Revised January 2025.)
- March 2024
- Teaching Note
'Storrowed': A Generative AI Exercise
By: Mitchell Weiss
Teaching Note for HBS Exercise No. 824-188. “Storrowed” is an exercise to help participants raise their proficiency with generative AI. It begins by highlighting a problem: trucks getting wedged underneath bridges in Boston, Massachusetts on the city’s Storrow Drive.... View Details
- 2025
- Article
Humor as a Window into Generative AI Bias
By: Roger Samure, Julian De Freitas and Stefano Puntoni
A preregistered audit of 600 images by generative AI across 150 different prompts explores the link between humor and discrimination in consumer-facing AI solutions. When ChatGPT updates images to make them “funnier”, the prevalence of stereotyped groups changes. While... View Details
Samure, Roger, Julian De Freitas, and Stefano Puntoni. "Humor as a Window into Generative AI Bias." Art. 1326. Scientific Reports 15 (2025).
- 2025
- Working Paper
The Impact of Input Inaccuracy on Leveraging AI Tools: Evidence from Algorithmic Labor Scheduling
By: Caleb Kwon, Antonio Moreno and Ananth Raman
Problem Definition: Considerable academic and practitioner attention is placed on the value of ex-post interactions (i.e., overrides) in the human-AI interface. In contrast, relatively little attention has been paid to ex-ante human-AI interactions (e.g., the... View Details
Kwon, Caleb, Antonio Moreno, and Ananth Raman. "The Impact of Input Inaccuracy on Leveraging AI Tools: Evidence from Algorithmic Labor Scheduling." Working Paper, January 2025.