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  • October 2021 (Revised June 2022)
  • Case

PittaRosso: Artificial Intelligence-Driven Pricing and Promotion

By: Ayelet Israeli
PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once... View Details
Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; AI; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
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Israeli, Ayelet. "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion." Harvard Business School Case 522-046, October 2021. (Revised June 2022.)
  • 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
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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.
  • 26 Mar 2018
  • Research & Ideas

To Motivate Employees, Give an Unexpected Bonus (or Penalty)

employees make or how many units they produce. “The objective performance measures don’t take into consideration whether the machine broke down or whether someone is still learning the job,” Gallani... View Details
Keywords: by Michael Blanding; Manufacturing
  • March 2023 (Revised March 2025)
  • Case

Accelerating AI Adoption in the U.S. Air Force

By: Maria P. Roche and Alexander Farrow
In August 2022, the Pentagon tasked U.S. Air Force Captain Victor Lopez to launch a new office for AFWERX, an Air Force innovation unit that leveraged commercial developers and military talent to acquire advanced technologies. This task was particularly arduous because... View Details
Keywords: Technological Innovation; Organizational Design; AI and Machine Learning; Adoption; Technology Adoption; United States
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Roche, Maria P., and Alexander Farrow. "Accelerating AI Adoption in the U.S. Air Force." Harvard Business School Case 723-429, March 2023. (Revised March 2025.)
  • Research Summary

Overview

By: Ashley V. Whillans
Engaged with field work in East Africa, South Asia, and in several large hybrid organizations in the United States, Professor Whillans places a focus on exploring questions with strong theoretical motivation in the social psychological literature and relevant... View Details
  • February 2020
  • Technical Note

Talent Management and the Future of Work

By: William R. Kerr and Gorick Ng
The nature of work is changing—and it is changing rapidly. Few days go by without industry giants such as Amazon and AT&T announcing plans to invest billions of dollars towards retraining nearly half of their respective workforces for jobs of the future. What changes... View Details
Keywords: Human Resource Management; Human Capital Development; Human Resource Practices; Talent; Talent Acquisition; Talent Development; Talent Development And Retention; Talent Management; Talent Retention; Labor Flows; Labor Management; Labor Market; Strategy Development; Strategy Management; Strategy Execution; Strategy And Execution; Strategic Change; Transformations; Organization; Organization Alignment; Organization Design; Organizational Adaptation; Organizational Effectiveness; Management Challenges; Management Of Business And Political Risk; Change Leadership; Future Of Work; Future; Skills Gap; Skills Development; Skills; Offshoring And Outsourcing; Investment; Capital Allocation; Work; Work Culture; Work Force Management; Work/life Balance; Work/family Balance; Work-family Boundary Management; Workers; Worker Productivity; Worker Performance; Work Engagement; Work Environment; Work Environments; Productivity; Organization Culture; Soft Skills; Technology Management; Technological Change; Technological Change: Choices And Consequences; Technology Diffusion; Disruptive Technology; Global Business; Global; Workplace; Workplace Context; Workplace Culture; Workplace Wellness; Collaboration; Competencies; Productivity Gains; Digital; Digital Transition; Competitive Dynamics; Competitiveness; Competitive Strategy; Data Analytics; Data; Data Management; Data Strategy; Data Protection; Aging Society; Diversity; Diversity Management; Millennials; Communication Complexity; Communication Technologies; International Business; Work Sharing; Global Competitiveness; Global Corporate Cultures; Intellectual Property; Intellectual Property Management; Intellectual Property Protection; Intellectual Capital And Property Issues; Globalization Of Supply Chain; Inequality; Recruiting; Hiring; Hiring Of Employees; Training; Job Cuts And Outsourcing; Job Performance; Job Search; Job Design; Job Satisfaction; Jobs; Employee Engagement; Employee Attitude; Employee Benefits; Employee Compensation; Employee Fairness; Employee Relationship Management; Employee Retention; Employee Selection; Employee Motivation; Employee Feedback; Employee Coordination; Employee Performance Management; Employee Socialization; Process Improvement; Application Performance Management; Stigma; Institutional Change; Candidates; Digital Enterprise; Cultural Adaptation; Cultural Change; Cultural Diversity; Cultural Context; Cultural Strategies; Cultural Psychology; Cultural Reform; Performance; Performance Effectiveness; Performance Management; Performance Evaluation; Performance Appraisal; Performance Feedback; Performance Measurement; Performance Metrics; Performance Measures; Performance Efficiency; Efficiency; Performance Analysis; Performance Appraisals; Performance Improvement; Automation; Artificial Intelligence; Technology Companies; Managerial Processes; Skilled Migration; Assessment; Human Resources; Management; Human Capital; Talent and Talent Management; Retention; Demographics; Labor; Strategy; Change; Change Management; Transformation; Organizational Change and Adaptation; Organizational Culture; Working Conditions; Information Technology; Technology Adoption; Disruption; Economy; Competition; Globalization; AI and Machine Learning; Digital Transformation
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Kerr, William R., and Gorick Ng. "Talent Management and the Future of Work." Harvard Business School Technical Note 820-084, February 2020.
  • 28 Apr 2022
  • Research & Ideas

Can You Buy Creativity in the Gig Economy?

gauged by monitoring nearly 1 million reader reviews using, in part, supervised machine learning in addition to searching for keywords such as “original,” “creative,” “surprisingly clever,” “innovative,” and... View Details
Keywords: by Pamela Reynolds
  • February 2024 (Revised January 2025)
  • Case

AGENTS.inc: Pathways to Growth at an AI Startup

By: Frank Nagle, Manuel Hoffmann, Karoline Ströhlein and Susan Pinckney
The case describes the history of AGENTS.inc. Despite being a small startup, with only four employees, that had never had a funding round, the company boasted an impressive client portfolio including multiple Fortune 500 companies. While AGENTS.inc had been an early... View Details
Keywords: Business Growth and Maturation; Business Model; Business Startups; Small Business; Transformation; Customer Focus and Relationships; Decisions; Entrepreneurship; Venture Capital; Financial Strategy; AI and Machine Learning; Digital Platforms; Technological Innovation; Copyright; Management; Growth and Development; Market Timing; Ownership; Risk and Uncertainty; Competition; Open Source Distribution; Entrepreneurial Finance; Computer Industry; Europe; Germany
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Nagle, Frank, Manuel Hoffmann, Karoline Ströhlein, and Susan Pinckney. "AGENTS.inc: Pathways to Growth at an AI Startup." Harvard Business School Case 724-444, February 2024. (Revised January 2025.)
  • 25 May 2021
  • Research & Ideas

White Airbnb Hosts Earn More. Can AI Shrink the Racial Gap?

Airbnb began offering a free tool to help all hosts set reasonable rates. The real-time, “smart pricing” program uses machine learning to automatically adjust the property’s nightly fees by considering a... View Details
Keywords: by Lane Lambert; Technology; Accommodations
  • 15 May 2017
  • Sharpening Your Skills

The Promises and Limitations of Big Data

services firms are using digital information about their customers to offer them a whole new range of customized products under the category of fintech. Cities are using data from Google Street View to guide economic development. And companies are finding that in some... View Details
Keywords: by Sean Silverthorne; Financial Services; Utilities; Public Administration; Health
  • June 2023 (Revised July 2023)
  • Case

Social Media Background Screening at Fama Technologies

By: Joseph Pacelli, Jillian Grennan and Alexis Lefort
Fama Technologies is an online screening company that uses AI to analyze job applicants' publicly available online content for signs of risk and culture fit. The case opens with Ben Mones, founder and CEO, looking to secure funding from venture firms. He is running... View Details
Keywords: Human Resources; Recruitment; Retention; Selection and Staffing; Organizational Culture; Talent and Talent Management; AI and Machine Learning; Social Media; Venture Capital; Entrepreneurship; United States
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Pacelli, Joseph, Jillian Grennan, and Alexis Lefort. "Social Media Background Screening at Fama Technologies." Harvard Business School Case 123-010, June 2023. (Revised July 2023.)
  • January 2024 (Revised January 2025)
  • Case

Huawei: Resilience amid Autarky and Adversity

By: William C. Kirby and Daniel Fu
In September 2023, Huawei made a dramatic return to the global smartphone space with the launch of its Mate 60 Pro smartphone, equipped with an indigenously designed, 7nm chip. This came despite a myriad of export controls and restrictions imposed against the company... View Details
Keywords: International Strategy; Semiconductors; Smartphone; Government And Politics; Government And Business; Digital Infrastructure; 5G; Political Risk; Business and Government Relations; Global Strategy; Multinational Firms and Management; Governing Rules, Regulations, and Reforms; AI and Machine Learning; Mobile and Wireless Technology; Leadership; Retirement; Corporate Strategy; Technology Industry; China; United States; Europe; Asia; Middle East
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Kirby, William C., and Daniel Fu. "Huawei: Resilience amid Autarky and Adversity." Harvard Business School Case 324-069, January 2024. (Revised January 2025.)
  • October 2019
  • Case

Leading Bank Leumi into the Future

By: Joshua D. Margolis, Allison M. Ciechanover, Nicole Keller and Danielle Golan
An unlikely but highly effective leader of a traditional bank, Rakefet Russak-Aminoach, simultaneously leads a classic change effort and an unconventional effort to innovate. She focuses her initial energy on making the bank more efficient in the face of industry... View Details
Keywords: Mobile Banking; Digital Banking; Fintech; Startup; Financial Services; Artificial Intelligence; Innovation; Efficiency; Organizational Change; Personal Development; Female Ceo; Banks and Banking; Mobile and Wireless Technology; Leadership; Organizational Change and Adaptation; Innovation and Invention; Disruption; Information Technology; Opportunities; Performance Effectiveness; Personal Development and Career; AI and Machine Learning; Financial Services Industry; Banking Industry; Israel
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Margolis, Joshua D., Allison M. Ciechanover, Nicole Keller, and Danielle Golan. "Leading Bank Leumi into the Future." Harvard Business School Case 420-063, October 2019.
  • 2024
  • Conference Paper

Quantifying Uncertainty in Natural Language Explanations of Large Language Models

By: Himabindu Lakkaraju, Sree Harsha Tanneru and Chirag Agarwal
Large Language Models (LLMs) are increasingly used as powerful tools for several high-stakes natural language processing (NLP) applications. Recent prompting works claim to elicit intermediate reasoning steps and key tokens that serve as proxy explanations for LLM... View Details
Keywords: Large Language Model; AI and Machine Learning
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Lakkaraju, Himabindu, Sree Harsha Tanneru, and Chirag Agarwal. "Quantifying Uncertainty in Natural Language Explanations of Large Language Models." Paper presented at the Society for Artificial Intelligence and Statistics, 2024.
  • 2022
  • Article

Efficiently Training Low-Curvature Neural Networks

By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret
Standard deep neural networks often have excess non-linearity, making them susceptible to issues such as low adversarial robustness and gradient instability. Common methods to address these downstream issues, such as adversarial training, are expensive and often... View Details
Keywords: AI and Machine Learning
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Srinivas, Suraj, Kyle Matoba, Himabindu Lakkaraju, and Francois Fleuret. "Efficiently Training Low-Curvature Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) (2022).
  • October 2024
  • Technical Note

Prompt Engineering

By: Michael Parzen and Jo Ellery
This note covers the basics of prompt engineering, a key tool for making use of modern generative AI. We discuss the principles of prompt engineering and illustrate these principles with techniques for asking questions. We further list the types of prompts that can be... View Details
Keywords: Large Language Model; AI and Machine Learning
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Parzen, Michael, and Jo Ellery. "Prompt Engineering." Harvard Business School Technical Note 625-056, October 2024.
  • April 2023
  • Article

On the Privacy Risks of Algorithmic Recourse

By: Martin Pawelczyk, Himabindu Lakkaraju and Seth Neel
As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely beneficial to affected... View Details
Keywords: Recourse; Privacy Threats; AI and Machine Learning; Information
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Pawelczyk, Martin, Himabindu Lakkaraju, and Seth Neel. "On the Privacy Risks of Algorithmic Recourse." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 206 (April 2023).
  • July 2024
  • Article

AI, ROI, and Sales Productivity

By: Frank V. Cespedes
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
Keywords: ROI; AI and Machine Learning; Sales; Investment Return
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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
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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).
  • September 23, 2024
  • Article

AI Wants to Make You Less Lonely. Does It Work?

By: Julian De Freitas
Keywords: AI and Machine Learning; Well-being
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De Freitas, Julian. "AI Wants to Make You Less Lonely. Does It Work?" Wall Street Journal (September 23, 2024), R.11.
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