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Publications

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  • All HBS Web  (1,049)
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  • All HBS Web  (1,049)
    • People  (1)
    • News  (187)
    • Research  (682)
    • Events  (13)
    • Multimedia  (3)
  • Faculty Publications  (564)
← Page 31 of 1,049 Results →
  • May–June 2024
  • Article

Should Your Brand Hire a Virtual Influencer?

By: Serim Hwang, Shunyuan Zhang, Xiao Liu and Kannan Srinivasan
Followers respond more favorably to sponsored posts by virtual influencers versus those by humans, costs are lower, and creating an influencer from scratch allows marketers to introduce more diversity. View Details
Keywords: Social Media; AI and Machine Learning; Brands and Branding; Power and Influence
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Hwang, Serim, Shunyuan Zhang, Xiao Liu, and Kannan Srinivasan. "Should Your Brand Hire a Virtual Influencer?" Harvard Business Review 102, no. 3 (May–June 2024): 56–60.
  • 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
Keywords: AI and Machine Learning; Behavior; Time Management
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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
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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
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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
Keywords: AI and Machine Learning; Organizational Culture; Performance Effectiveness
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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
Keywords: AI and Machine Learning; Attitudes; Perception
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De Freitas, Julian, A. Ragnhildstveit, and A.K. Uğuralp. "Stigma Against AI Companion Applications." 53rd Association for Consumer Research Annual Conference, Denver, CO, October 20–22, 2022.
  • Web

Eva Tuecke | MBA

Currently, I am particularly excited by challenges in AI interpretability, healthtech, and applications of machine learning to quantum computing. LinkedIn: Eva Tuecke View Details
  • 01 Oct 1997
  • News

Expanded Elective Curriculum Offers Students A Wealth of Choices

finest." Field-Based Learning Expanded field-based learning opportunities now include more field studies, faculty-initiated research projects in which students may participate, and fieldwork within standard... View Details
  • 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
Keywords: Technological Innovation; AI and Machine Learning; Open Source Distribution; Policy
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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
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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
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Satchu, Reza, and Patrick Sanguineti. "Ada: Cultivating Investors." Harvard Business School Case 824-090, September 2023.
  • January–February 2025
  • Article

Why People Resist Embracing AI

By: Julian De Freitas
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
Keywords: AI and Machine Learning; Technology Adoption; Perception
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De Freitas, Julian. "Why People Resist Embracing AI." Harvard Business Review 103, no. 1 (January–February 2025): 52–56.
  • March–April 2025
  • Article

Strategy in an Era of Abundant Expertise: How to Thrive When AI Makes Knowledge and Know-How Cheaper and Easier to Access

By: Bobby Yerramilli-Rao, John Corwin, Yang Li and Karim R. Lakhani
The AI era is in its early stages, and the technology is evolving extremely quickly. Providers are rapidly introducing AI "copilots," "bots," and "assistants" into applications to augment employees' workflows. Examples include GitHub Copilot for coding, ServiceNow... View Details
Keywords: AI; AI and Machine Learning; Performance Productivity; Experience and Expertise; Technology Adoption
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Yerramilli-Rao, Bobby, John Corwin, Yang Li, and Karim R. Lakhani. "Strategy in an Era of Abundant Expertise: How to Thrive When AI Makes Knowledge and Know-How Cheaper and Easier to Access." Harvard Business Review 103, no. 2 (March–April 2025): 72–81.
  • September–October 2024
  • Article

The Crowdless Future? Generative AI and Creative Problem-Solving

By: Léonard Boussioux, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic and Karim R. Lakhani
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
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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.
  • 01 Jun 2015
  • News

The Military and the MBA: Gene Markowski (MBA 1973)

in 2013. I was stationed in a tank unit out in Colorado Springs when the Vietnam War started up. I didn’t think I wanted to be in a tank in Vietnam, so I volunteered to go to flight school. Six months later, I was in combat. I was a 24-year-old captain View Details
Keywords: National Security and International Affairs; Government
  • October 14, 2023
  • Article

Will Consumers Buy Selfish Self-Driving Cars?

By: Julian De Freitas
Keywords: AI and Machine Learning; Ethics; Technological Innovation; Safety; Auto Industry
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De Freitas, Julian. "Will Consumers Buy Selfish Self-Driving Cars?" Wall Street Journal (October 14, 2023), C5.
  • Web

Cameron Stone | MBA

opportunity to add more business and leadership understanding to my technical background, work alongside innovative, like-minded peers, and learn how to identify and tackle issues critical to society!” Tech areas of interest: View Details
  • 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
Keywords: AI and Machine Learning; Gender; Equality and Inequality; Technology Adoption; Behavior
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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.)
  • 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
  • 16 Nov 2020
  • Blog Post

Flatiron School: Reflections from Summer 2020

Birchbox, Young Invincibles, Color Camp, Women 2.0 and Casper. WHAT WERE YOUR GOALS FOR THE SUMMER? Rocio Wu (MBA 2020): Learning python and machine learning had always been on... View Details
Keywords: All Industries
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