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Show Results For
- All HBS Web
(986)
- People (1)
- News (155)
- Research (662)
- Events (13)
- Multimedia (3)
- Faculty Publications (567)
- 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.)
- 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.
- 2022
- Working Paper
The Evolution of ESG Reports and the Role of Voluntary Standards
By: Ethan Rouen, Kunal Sachdeva and Aaron Yoon
We examine the evolution of ESG reports of S&P 500 firms from 2010 to 2021. The
percentage of firms releasing these voluntary disclosures increased from 35% to 86%
during this period, although the length of these documents experienced more modest
growth. Using a... View Details
Keywords: Voluntary Disclosure; Textual Analysis; Modeling And Analysis; Corporate Social Responsibility and Impact; AI and Machine Learning; Accounting
Rouen, Ethan, Kunal Sachdeva, and Aaron Yoon. "The Evolution of ESG Reports and the Role of Voluntary Standards." Harvard Business School Working Paper, No. 23-024, October 2022.
- 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).
- Working Paper
Shifting Work Patterns with Generative AI
By: Eleanor W. Dillon, Sonia Jaffe, Nicole Immorlica and Christopher T. Stanton
We present evidence on how generative AI changes the work patterns of knowledge workers using
data from a 6-month-long, cross-industry, randomized field experiment. Half of the 7,137 workers
in the study received access to a generative AI tool integrated into the... View Details
Dillon, Eleanor W., Sonia Jaffe, Nicole Immorlica, and Christopher T. Stanton. "Shifting Work Patterns with Generative AI." NBER Working Paper Series, No. 33795, May 2025. (Conditionally Accepted at American Economic Review: Insights .)
- January 2025
- Technical Note
AI vs Human: Analyzing Acceptable Error Rates Using the Confusion Matrix
By: Tsedal Neeley and Tim Englehart
This technical note introduces the confusion matrix as a foundational tool in artificial intelligence (AI) and large language models (LLMs) for assessing the performance of classification models, focusing on their reliability for decision-making. A confusion matrix... View Details
Keywords: Reliability; Confusion Matrix; AI and Machine Learning; Decision Making; Measurement and Metrics; Performance
Neeley, Tsedal, and Tim Englehart. "AI vs Human: Analyzing Acceptable Error Rates Using the Confusion Matrix." Harvard Business School Technical Note 425-049, January 2025.
- 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.
- November 2, 2021
- Article
The Cultural Benefits of Artificial Intelligence in the Enterprise
By: Sam Ransbotham, François Candelon, David Kiron, Burt LaFountain and Shervin Khodabandeh
The 2021 MIT SMR-BCG report identifies a wide range of AI-related cultural benefits at both the team and organizational levels. Whether it’s reconsidering business assumptions or empowering teams, managing the dynamics across culture, AI use, and organizational... View Details
Ransbotham, Sam, François Candelon, David Kiron, Burt LaFountain, and Shervin Khodabandeh. "The Cultural Benefits of Artificial Intelligence in the Enterprise." MIT Sloan Management Review, Big Ideas Artificial Intelligence and Business Strategy Initiative (website) (November 2, 2021). (Findings from the 2021 Artificial Intelligence and Business Strategy Global Executive Study and Research Project.)
- 20 Oct 2022 - 22 Oct 2022
- Talk
Stigma Against AI Companion Applications
By: Julian De Freitas, A. Ragnhildstveit and A.K. Uğuralp
- January–February 2025
- Article
Why People Resist Embracing AI
The success of AI depends not only on its capabilities, which are becoming more advanced each day, but on people’s willingness to harness them. Unfortunately, many people view AI negatively, fearing it will cause job losses, increase the likelihood that their personal... View Details
De Freitas, Julian. "Why People Resist Embracing AI." Harvard Business Review 103, no. 1 (January–February 2025): 52–56.
- July 2024
- Case
The Voice Wars Continues 2024: Hey Google vs. Alexa vs. Siri vs. ChatGPT
By: David B. Yoffie and Sarah von Bargen
In 2024, the Voice War was transforming from a relatively simple index-based technology system, which relied on a list of commands and answers, to a generative AI system, which offered the promise to enable free flowing conversations between people and machines. The... View Details
Yoffie, David B., and Sarah von Bargen. "The Voice Wars Continues 2024: Hey Google vs. Alexa vs. Siri vs. ChatGPT." Harvard Business School Case 725-352, July 2024.
- January 2024
- Case
The Financial Times (FT) and Generative AI
By: Andrew Rashbass, Ramon Casadesus-Masanell and Jordan Mitchell
In September 2023, John Ridding, CEO of the Financial Times, was considering the possible impact of Generative AI on the industry and his business. Having navigated successfully the seismic shift from print to digital, and reporting record results, the company... View Details
Keywords: AI and Machine Learning; Technology Adoption; Change Management; Journalism and News Industry
Rashbass, Andrew, Ramon Casadesus-Masanell, and Jordan Mitchell. "The Financial Times (FT) and Generative AI." Harvard Business School Case 724-410, January 2024.
- 11 Oct 2024
- Research & Ideas
How AI Could Ease the Refugee Crisis and Bring New Talent to Businesses
says. “What we’re asking is, can we build algorithms that will help find better matches that will allow people to integrate more easily?” The paper presents data from Switzerland and the United States that showed promise in using machine... 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.)
- June 2025
- Article
Ideation with Generative AI—In Consumer Research and Beyond
By: Julian De Freitas, G. Nave and Stefano Puntoni
The use of large language models (LLMs) in consumer research is rapidly evolving, with applications including synthetic data generation, data analysis, and more. However, their role in creative ideation—a cornerstone of consumer research—remains underexplored. Drawing... View Details
De Freitas, Julian, G. Nave, and Stefano Puntoni. "Ideation with Generative AI—In Consumer Research and Beyond." Journal of Consumer Research 51, no. 1 (June 2025): 18–31.
- June 2024
- Teaching Note
Numenta in 2020: The Future of AI
By: David B. Yoffie
In 2020, Numenta’s co-founder, Jeff Hawkins, completed his pathbreaking research on artificial intelligence. His co-founder and CEO, Donna Dubinsky, had to find a business model to monetize the technology. This teaching note explores the challenges of building a... View Details
- 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.
- 2023
- Article
On the Impact of Actionable Explanations on Social Segregation
By: Ruijiang Gao and Himabindu Lakkaraju
As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research... View Details
Gao, Ruijiang, and Himabindu Lakkaraju. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.
- October 14, 2023
- Article
Will Consumers Buy Selfish Self-Driving Cars?
De Freitas, Julian. "Will Consumers Buy Selfish Self-Driving Cars?" Wall Street Journal (October 14, 2023), C5.