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Show Results For
- All HBS Web
(1,540)
- People (1)
- News (285)
- Research (979)
- Events (19)
- Multimedia (6)
- Faculty Publications (809)
- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I. Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details
Liang, Biyonka, and Iavor I. Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
- March 2025
- Supplement
Intuition Robotics: An AI Companion for Older Adults (B)
By: Amit Goldenberg, Elie Ofek and Orna Dan
Two years after Intuition Robotics opted to pursue a business-to-government contract with the New York State Office of the Aging, and put direct-to-consumer efforts on the back burner, it was at a crossroads. The partnership had been successful, and the company had... View Details
- February 2024
- Technical Note
AI Product Development Lifecycle
By: Michael Parzen, Jessie Li and Marily Nika
In this article, we will discuss the concept of AI Products, how they are changing our daily lives, how the field of AI & Product Management is evolving, and the AI Product Development Lifecycle. View Details
Keywords: Artificial Intelligence; Product Management; Product Life Cycle; Technology; AI and Machine Learning; Product Development
Parzen, Michael, Jessie Li, and Marily Nika. "AI Product Development Lifecycle." Harvard Business School Technical Note 624-070, February 2024.
- March 2025
- Case
Harvey: AI for Lawyers
By: Suraj Srinivasan, Charles Krumholz and Radhika Kak
In early 2025, Winston Weinberg and Gabe Pereyra, co-founders of Harvey AI, reflected on the company’s meteoric rise as a pioneer in AI-powered legal technology. Since its founding in 2022, Harvey had transformed how lawyers approached research, drafting, and document... View Details
Keywords: Innovation Strategy; Business Startups; AI and Machine Learning; Technological Innovation; Growth and Development Strategy; Product Positioning; Legal Services Industry; Technology Industry; New York (city, NY); San Francisco; London
Srinivasan, Suraj, Charles Krumholz, and Radhika Kak. "Harvey: AI for Lawyers." Harvard Business School Case 125-087, March 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.
- 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
Satchu, Reza, and Patrick Sanguineti. "Ada: Cultivating Investors." Harvard Business School Case 824-090, September 2023.
- January 2025
- Case
Moderna: Democratizing Artificial Intelligence
By: Iavor I. Bojinov, Karim R. Lakhani, Annika Hildebrandt and James Weber
The case study examines Moderna's journey in democratizing artificial intelligence (AI), particularly generative AI, across its workforce. It details the company's "digital-first, AI-focused" approach, including the rollout of OpenAI's ChatGPT Enterprise to all... View Details
Keywords: AI and Machine Learning; Technology Adoption; Innovation Strategy; Governance Controls; Biotechnology Industry
Bojinov, Iavor I., Karim R. Lakhani, Annika Hildebrandt, and James Weber. "Moderna: Democratizing Artificial Intelligence." Harvard Business School Case 625-070, January 2025.
- May 2024
- Article
The Health Risks of Generative AI-Based Wellness Apps
By: Julian De Freitas and G. Cohen
Artifcial intelligence (AI)-enabled chatbots are increasingly being used to
help people manage their mental health. Chatbots for mental health and
particularly ‘wellness’ applications currently exist in a regulatory ‘gray area’.
Indeed, most generative AI-powered... View Details
Keywords: AI and Machine Learning; Well-being; Governing Rules, Regulations, and Reforms; Applications and Software
De Freitas, Julian, and G. Cohen. "The Health Risks of Generative AI-Based Wellness Apps." Nature Medicine 30, no. 5 (May 2024): 1269–1275.
- November 2024
- Supplement
AlphaGo (B): Birth of a New Intelligence
By: Shikhar Ghosh and Shweta Bagai
This case, the second in a three-part series, explores DeepMind's evolution from developing game-specific AI to more generalized learning systems. Following AlphaGo's 2017 victory over the Go world champion, DeepMind introduced two revolutionary systems that eliminated... View Details
Keywords: AI and Machine Learning; Games, Gaming, and Gambling; Technological Innovation; Disruptive Innovation; Innovation Leadership; Information Technology Industry; United States; Russia; China
Ghosh, Shikhar, and Shweta Bagai. "AlphaGo (B): Birth of a New Intelligence." Harvard Business School Supplement 825-074, November 2024.
- December 2018
- Teaching Note
Autonomous Vehicles: The Rubber Hits the Road…but When?
By: William Kerr and James Palano
The autonomous vehicles have enormous implications for business and society. But, despite the headline-laden attention paid to the technology, there remain more questions than answers. Students will learn about the complex industry and have explicit discussions about... View Details
- 2024
- Working Paper
Scaling Core Earnings Measurement with Large Language Models
By: Matthew Shaffer and Charles CY Wang
We study the application of large language models (LLMs) to the estimation of core earnings, i.e., a firm's persistent profitability from its core business activities. This construct is central to investors' assessments of economic performance and valuations. However,... View Details
Keywords: Large Language Models; AI and Machine Learning; Accounting; Profit; Corporate Disclosure; Analytics and Data Science; Measurement and Metrics
Shaffer, Matthew, and Charles CY Wang. "Scaling Core Earnings Measurement with Large Language Models." Working Paper, November 2024.
- 06 May 2015
- What Do You Think?
Are You Ready for Personalized Predictive Analytics?
Summing Up Personal Predictive Analytics: Should We Be Careful What We Wish For? The world of continuous monitoring of numerous sensors for machines and humans, limitless information storage capacity, View Details
Keywords: by James Heskett
- 2023
- Working Paper
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details
Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
- October 2019
- Case
Feeling Machines: Emotion AI at Affectiva
By: Shane Greenstein and John Masko
In 2016, Affectiva—a Boston-based emotion AI software company with a long track record of building emotion-sensing software for market research—had attempted to expand into new verticals by releasing a mobile software development kit (SDK) that downloaders could adapt... View Details
Keywords: Artificial Intelligence; Market Research; Business Model; Finance; Revenue; Decision Making; Risk and Uncertainty; Market Entry and Exit; Applications and Software; AI and Machine Learning; Information Technology Industry; Auto Industry; United States
Greenstein, Shane, and John Masko. "Feeling Machines: Emotion AI at Affectiva." Harvard Business School Case 620-058, October 2019.
- June 2025
- Case
Accounting for OpenAI at Microsoft
By: Jonas Heese, Joseph Pacelli, Nicole Zelazko and Michael Norris
In early 2025, Microsoft was evaluating the impact of its $14 billion investment in OpenAI. As OpenAI’s computing needs expanded, Microsoft positioned Azure as the exclusive provider for training and inference of their large language models. Despite the scale of the... View Details
- 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).
- 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.
- April 2021
- Case
Distinct Software
By: Das Narayandas, Arijit Sengupta and Jonathan Wray
Distinct Software (disguised name), a global enterprise software company, is at an important point in its growth trajectory where the luster of its mantra of “grow and win at any cost” has dimmed with increasing competition and margin pressures. To help navigate its... View Details
Keywords: Artificial Intelligence; Marketing; Sales; Performance Productivity; Technological Innovation; AI and Machine Learning
Narayandas, Das, Arijit Sengupta, and Jonathan Wray. "Distinct Software." Harvard Business School Case 521-101, April 2021.
- March 2025 (Revised April 2025)
- Case
Perplexity: Redefining Search
By: Suraj Srinivasan, Michelle Hu, Sriraghav Srinivasan and Radhika Kak
By early 2025, Perplexity had rapidly evolved from a modest startup into a popular "answer engine" valued at $9 billion. The company had boldly positioned itself as the disruptor to Google aiming to redefine search for the AI age. Through novel AI... View Details
Keywords: AI and Machine Learning; Venture Capital; Innovation Leadership; Technological Innovation; Internet and the Web; Business Startups; Competitive Strategy; Business Model; Technology Industry; United States
Srinivasan, Suraj, Michelle Hu, Sriraghav Srinivasan, and Radhika Kak. "Perplexity: Redefining Search." Harvard Business School Case 125-093, March 2025. (Revised April 2025.)
- January 2025 (Revised April 2025)
- Case
Duolingo: On a 'Streak'
By: Jeffrey F. Rayport, Nicole Tempest Keller and Nicole Luo
In December 2024, Severin Hacker, Co-Founder and Chief Technology Officer of Duolingo, reflected on the remarkable evolution of the language-learning app he helped launch in 2011. As the #1 most downloaded education app in the world, Duolingo had over 100 million... View Details
Keywords: Learning; AI and Machine Learning; Growth and Development Strategy; Motivation and Incentives; Diversification; Business Model; Market Entry and Exit; Technology Industry; Education Industry; United States
Rayport, Jeffrey F., Nicole Tempest Keller, and Nicole Luo. "Duolingo: On a 'Streak'." Harvard Business School Case 825-097, January 2025. (Revised April 2025.)