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(1,221)
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- Faculty Publications (586)
Show Results For
- All HBS Web
(1,221)
- People (1)
- News (247)
- Research (702)
- Events (17)
- Multimedia (9)
- Faculty Publications (586)
- August 2023
- Case
Beamery: Using Skills and AI to Modernize HR
By: Boris Groysberg, Alexis Lefort, Susan Pinckney and Carolina Bartunek
Unicorn human relationships startup Beamery evaluates it's growth versus depth strategy as its strategic partners and customers could become future competitors in a quickly changing AI based human resources and talent management industry View Details
Keywords: Acquisition; Business Growth and Maturation; Business Startups; Competency and Skills; Experience and Expertise; Talent and Talent Management; Customers; Nationality; Learning; Entrepreneurship; Employee Relationship Management; Recruitment; Retention; Selection and Staffing; Values and Beliefs; Cross-Cultural and Cross-Border Issues; Analytics and Data Science; Applications and Software; Disruptive Innovation; Technological Innovation; Job Offer; Job Search; Job Design and Levels; Employment; Human Capital; Europe; United Kingdom; United States
Groysberg, Boris, Alexis Lefort, Susan Pinckney, and Carolina Bartunek. "Beamery: Using Skills and AI to Modernize HR." Harvard Business School Case 424-004, August 2023.
- 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.
- January 2025
- Article
Reducing Prejudice with Counter-stereotypical AI
By: Erik Hermann, Julian De Freitas and Stefano Puntoni
Based on a review of relevant literature, we propose that the proliferation of AI with human-like and social features presents an unprecedented opportunity to address the underlying cognitive and affective drivers of prejudice. An approach informed by the psychology of... View Details
Keywords: Prejudice and Bias; AI and Machine Learning; Interpersonal Communication; Social and Collaborative Networks
Hermann, Erik, Julian De Freitas, and Stefano Puntoni. "Reducing Prejudice with Counter-stereotypical AI." Consumer Psychology Review 8, no. 1 (January 2025): 75–86.
- October 20, 2020
- Article
Expanding AI's Impact with Organizational Learning
By: Sam Ransbotham, Shervin Khodabandeh, David Kiron, François Candelon, Michael Chu and Burt LaFountain
Most companies developing AI capabilities have yet to gain significant financial benefits from their efforts. Only when organizations add the ability to learn with AI do significant benefits become likely. View Details
Ransbotham, Sam, Shervin Khodabandeh, David Kiron, François Candelon, Michael Chu, and Burt LaFountain. "Expanding AI's Impact with Organizational Learning." MIT Sloan Management Review, Big Ideas Artificial Intelligence and Business Strategy Initiative (website) (October 20, 2020). (Findings from the 2020 Artificial Intelligence
Global Executive Study and Research Project.)
- 2024
- Working Paper
The Value of AI Innovations
By: Wilbur Xinyuan Chen, Terrence Tianshuo Shi and Suraj Srinivasan
We study the value of AI innovations as it diffuses across general and application sectors, using the United States Patent and Trademark Office’s (USPTO) AI patent dataset. Investors value these innovations more than others, as AI patents exhibit a 9% value premium,... View Details
Keywords: AI and Machine Learning; Valuation; Technological Innovation; Open Source Distribution; Patents; Policy; Knowledge Sharing; Technology Industry
Chen, Wilbur Xinyuan, Terrence Tianshuo Shi, and Suraj Srinivasan. "The Value of AI Innovations." Harvard Business School Working Paper, No. 24-069, May 2024.
- 2021
- Conference Presentation
An Algorithmic Framework for Fairness Elicitation
By: Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Leon Roth, Logan Stapleton and Zhiwei Steven Wu
We consider settings in which the right notion of fairness is not captured by simple mathematical definitions (such as equality of error rates across groups), but might be more complex and nuanced and thus require elicitation from individual or collective stakeholders.... View Details
Jung, Christopher, Michael J. Kearns, Seth Neel, Aaron Leon Roth, Logan Stapleton, and Zhiwei Steven Wu. "An Algorithmic Framework for Fairness Elicitation." Paper presented at the 2nd Symposium on Foundations of Responsible Computing (FORC), 2021.
- February 2019
- Case
Miroglio Fashion (A)
By: Sunil Gupta and David Lane
Francesco Cavarero, chief information officer of Miroglio Fashion, Italy’s third-largest retailer of women’s apparel, was trying to bring analytical rigor to the company’s forecasting and inventory management decisions. But fashion is inherently hard to predict. Can... View Details
Keywords: Inventory Management; Demand Forecasting; Artificial Intelligence; Machine Learning; Forecasting and Prediction; Operations; Management; Decision Making; AI and Machine Learning; Apparel and Accessories Industry; Apparel and Accessories Industry
Gupta, Sunil, and David Lane. "Miroglio Fashion (A)." Harvard Business School Case 519-053, February 2019.
- November 2023
- Case
Copilot(s): Generative AI at Microsoft and GitHub
By: Frank Nagle, Shane Greenstein, Maria P. Roche, Nataliya Langburd Wright and Sarah Mehta
This case tells the story of Microsoft’s 2018 acquisition of GitHub and the subsequent launch of GitHub Copilot, a tool that uses generative artificial intelligence to suggest snippets of code to software developers in real time. Set in late 2021, when Copilot was... View Details
Keywords: Business Ventures; Strategy; AI and Machine Learning; Applications and Software; Product Launch; Information Technology Industry; Technology Industry; Web Services Industry; United States; California
Nagle, Frank, Shane Greenstein, Maria P. Roche, Nataliya Langburd Wright, and Sarah Mehta. "Copilot(s): Generative AI at Microsoft and GitHub." Harvard Business School Case 624-010, November 2023.
- 2024
- Working Paper
Learning to Cover: Online Learning and Optimization with Irreversible Decisions
By: Alexander Jacquillat and Michael Lingzhi Li
Keywords: Buildings and Facilities; AI and Machine Learning; Geographic Location; Strategic Planning
Jacquillat, Alexander, and Michael Lingzhi Li. "Learning to Cover: Online Learning and Optimization with Irreversible Decisions." Working Paper, June 2024.
- June 2024
- Teaching Note
Beamery: Using Skills and AI to Modernize HR
By: Boris Groysberg, David Lane, Susan Pinckney and Alexis Lefort
Teaching Note for HBS Case No. 424-004. Unicorn human relationships startup Beamery evaluates it growth versus depth strategy as its strategic partners and customers could become future competitors in a quickly changing AI based human resources and talent management... View Details
Keywords: Analysis; Business Growth and Maturation; Business Model; Business Startups; Business Plan; Disruption; Transformation; Talent and Talent Management; Decisions; Diversity; Ethnicity; Gender; Nationality; Race; Residency; Higher Education; Learning; Entrepreneurship; Fairness; Cross-Cultural and Cross-Border Issues; Global Strategy; Growth and Development; AI and Machine Learning; Digital Platforms; Disruptive Innovation; Technological Innovation; Job Offer; Job Search; Knowledge Acquisition; Knowledge Use and Leverage; Product; Mission and Purpose; Strategic Planning; Problems and Challenges; Corporate Strategy; Equality and Inequality; Valuation; Value Creation; Employment Industry; United Kingdom
- 2024
- Working Paper
The Cram Method for Efficient Simultaneous Learning and Evaluation
By: Zeyang Jia, Kosuke Imai and Michael Lingzhi Li
We introduce the "cram" method, a general and efficient approach to simultaneous learning and evaluation using a generic machine learning (ML) algorithm. In a single pass of batched data, the proposed method repeatedly trains an ML algorithm and tests its empirical... View Details
Keywords: AI and Machine Learning
Jia, Zeyang, Kosuke Imai, and Michael Lingzhi Li. "The Cram Method for Efficient Simultaneous Learning and Evaluation." Working Paper, March 2024.
- 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
- Article
Who, When, and Why: A Machine Learning Approach to Prioritizing Students at Risk of Not Graduating High School on Time
By: Everaldo Aguiar, Himabindu Lakkaraju, Nasir Bhanpuri, David Miller, Ben Yuhas, Kecia Addison and Rayid Ghani
Aguiar, Everaldo, Himabindu Lakkaraju, Nasir Bhanpuri, David Miller, Ben Yuhas, Kecia Addison, and Rayid Ghani. "Who, When, and Why: A Machine Learning Approach to Prioritizing Students at Risk of Not Graduating High School on Time." Proceedings of the International Learning Analytics and Knowledge Conference 5th (2015).
- 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.
- April 12, 2023
- Article
Using AI to Adjust Your Marketing and Sales in a Volatile World
By: Das Narayandas and Arijit Sengupta
Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer... View Details
Keywords: Forecasting and Prediction; AI and Machine Learning; Consumer Behavior; Technology Adoption; Competitive Advantage
Narayandas, Das, and Arijit Sengupta. "Using AI to Adjust Your Marketing and Sales in a Volatile World." Harvard Business Review Digital Articles (April 12, 2023).
- March 2023
- Teaching Note
VideaHealth: Building the AI Factory
By: Karim R. Lakhani
Teaching Note for HBS Case No. 621-021. The case “VideaHealth: Building the AI Factory” examines the creation of dental startup VideaHealth (Videa) and the development of its artificial intelligence (AI)-led business strategy through the eyes of founder and CEO Florian... View Details
- TeachingInterests
Data Science and Artificial Intelligence for Leaders
By: Chiara Farronato
With artificial intelligence (AI)... View Details
- March 2024
- Exercise
'Storrowed': A Generative AI Exercise
By: Mitchell Weiss
"Storrowed" is an exercise to help participants raise their capacity and curiosity for generative AI. It focuses on generative AI for problem understanding and ideation, but can be adapted for use more broadly. Participants use generative AI tools to understand a... View Details
Weiss, Mitchell. "'Storrowed': A Generative AI Exercise." Harvard Business School Exercise 824-188, March 2024.
- 2025
- Working Paper
Narrative AI and the Human-AI Oversight Paradox in Evaluating Early-Stage Innovations
By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang
Do AI-generated narrative explanations enhance human oversight or diminish it? We investigate this question through a field experiment with 228 evaluators screening 48 early-stage innovations under three conditions: human-only, black-box AI recommendations without... View Details
Lane, Jacqueline N., Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh, and Pei-Hsin Wang. "Narrative AI and the Human-AI Oversight Paradox in Evaluating Early-Stage Innovations." Harvard Business School Working Paper, No. 25-001, August 2024. (Revised May 2025.)
- November 2023
- Article
Psychological Factors Underlying Attitudes toward AI Tools
By: Julian De Freitas, Stuti Agarwal, B. Schmitt and N. Haslam
What are the psychological factors driving attitudes toward AI tools, and how can resistance to AI systems be overcome when they are beneficial? In this perspective, we first organize the main sources of resistance into five main categories: opacity, emotionlessness,... View Details
De Freitas, Julian, Stuti Agarwal, B. Schmitt, and N. Haslam. "Psychological Factors Underlying Attitudes toward AI Tools." Nature Human Behaviour 7, no. 11 (November 2023): 1845–1854.