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Show Results For
- All HBS Web
(1,220)
- People (1)
- News (247)
- Research (702)
- Events (17)
- Multimedia (9)
- Faculty Publications (587)
- June 2024
- Case
Aidoc: Building a Hospital-Centric AI Platform
By: Ariel D. Stern and Susan Pinckney
In 2023, Israel-based AI health care company Aidoc evaluated its future. The company, founded in 2016, had grown from commercializing a single AI product for radiologists to a software platform that could detect 20 conditions and immediately notify care teams of... View Details
Keywords: Business Growth and Maturation; Business Model; Business Organization; Business Startups; Disruption; Cost vs Benefits; Decision Choices and Conditions; Decisions; Private Sector; Entrepreneurial Finance; Global Range; Global Strategy; Globalized Markets and Industries; Governance Compliance; Governance Controls; Governing and Advisory Boards; Policy; Medical Specialties; AI and Machine Learning; Digital Platforms; Digital Transformation; Technology Adoption; Disruptive Innovation; Innovation and Management; Innovation Strategy; Laws and Statutes; Growth and Development Strategy; Growth Management; Distribution; Product Development; Success; Performance Efficiency; Strategic Planning; Research and Development; Risk and Uncertainty; Business Strategy; Competitive Advantage; Value Creation; Health Industry; Israel
Stern, Ariel D., and Susan Pinckney. "Aidoc: Building a Hospital-Centric AI Platform." Harvard Business School Case 624-046, June 2024.
- December 1, 2021
- Article
Do You Know How Your Teams Get Work Done?
By: Rohan Narayana Murty, Rajath B. Das, Scott Duke Kominers, Arjun Narayan, Suraj Srinivasan, Tarun Khanna and Kartik Hosanagar
In a research study at four Fortune 500 companies, when managers were asked about their teams’ work, on average they either did not know or could not remember 60% of the work their teams do. This is a major problem because it can lead to unrealistic digital... View Details
Keywords: Leading Teams; Work Recall Gap; Machine Learning; Algorithms; Groups and Teams; Management; Technological Innovation
Murty, Rohan Narayana, Rajath B. Das, Scott Duke Kominers, Arjun Narayan, Suraj Srinivasan, Tarun Khanna, and Kartik Hosanagar. "Do You Know How Your Teams Get Work Done?" Harvard Business Review Digital Articles (December 1, 2021).
- September–October 2024
- Article
How AI Can Power Brand Management
By: Julian De Freitas and Elie Ofek
Marketers have begun experimenting with AI to improve their brand-management efforts. But unlike other marketing tasks, brand management involves more than just repeatedly executing one specialized function. Long considered the exclusive domain of creative talent, it... View Details
Keywords: Creativity; AI and Machine Learning; Brands and Branding; Product Positioning; Customer Focus and Relationships
De Freitas, Julian, and Elie Ofek. "How AI Can Power Brand Management." Harvard Business Review 102, no. 5 (September–October 2024): 108–114.
- 14 Aug 2017
- Conference Presentation
A Convex Framework for Fair Regression
By: Richard Berk, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel and Aaron Roth
We introduce a flexible family of fairness regularizers for (linear and logistic) regression problems. These regularizers all enjoy convexity, permitting fast optimization, and they span the range from notions of group fairness to strong individual fairness. By varying... View Details
Berk, Richard, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Roth. "A Convex Framework for Fair Regression." Paper presented at the 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), August 14, 2017.
- March 2019
- Teaching Note
Numenta: Inventing and (or) Commercializing AI
By: David B. Yoffie
This teaching notes accompanies the Numenta case, HBS No. 716-469. The focus is how to scale a new artificial intelligence technology, how to build a platform and overcome chicken-or-the-egg problems, and how to utilize open source software and licensing. View Details
- July–August 2025
- Article
Don’t Let an AI Failure Harm Your Brand
How companies market their AI systems affects the repercussions they face when their products fail. Marketers must promote their AI products with potential failure in mind. To do that, they must first understand consumers’ unique attitudes toward AI. Marketers who... View Details
Keywords: AI and Machine Learning; Brands and Branding; Product Marketing; Consumer Behavior; Attitudes
De Freitas, Julian. "Don’t Let an AI Failure Harm Your Brand." Harvard Business Review 103, no. 4 (July–August 2025): 126–133.
- 2025
- Working Paper
The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise
By: Fabrizio Dell'Acqua, Charles Ayoubi, Hila Lifshitz, Raffaella Sadun, Ethan Mollick, Lilach Mollick, Yi Han, Jeff Goldman, Hari Nair, Stew Taub and Karim R. Lakhani
We examine how artificial intelligence transforms the core pillars of collaboration—
performance, expertise sharing, and social engagement—through a pre-registered field
experiment with 776 professionals at Procter & Gamble, a global consumer packaged goods
company.... View Details
Keywords: Artificial Intelligence; Teamwork; Human-machine Interaction; Productivity; Skills; Innovation; Field Experiment; AI and Machine Learning; Groups and Teams; Competency and Skills; Performance Productivity; Collaborative Innovation and Invention; Product Development
Dell'Acqua, Fabrizio, Charles Ayoubi, Hila Lifshitz, Raffaella Sadun, Ethan Mollick, Lilach Mollick, Yi Han, Jeff Goldman, Hari Nair, Stew Taub, and Karim R. Lakhani. "The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise." Harvard Business School Working Paper, No. 25-043, March 2025.
- January 2025
- Supplement
The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation (B)
By: Tsedal Neeley, Levi Stroud, Ruth Page and Dave Habeeb
Pre-abstract:
This multimedia case should be assigned to students in advance of class. Instructors should consider the timing of making the (B) Case videos available to students, as they may reveal key case details.
Abstract: Florian Hillen, co-founder... View Details
Abstract: Florian Hillen, co-founder... View Details
Keywords: Diagnostics; Organization Design; Change Management; Disruption; Transformation; Health Care and Treatment; AI and Machine Learning; Technology Adoption; Technological Innovation; Management Style; Organizational Culture; Success; Technology Industry; Health Industry; United States
Neeley, Tsedal, Levi Stroud, Ruth Page, and Dave Habeeb. "The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation (B)." Harvard Business School Multimedia/Video Supplement 425-721, January 2025.
- January 2025
- Case
The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation (A)
By: Tsedal Neeley, Levi Stroud, Ruth Page and Dave Habeeb
Pre-abstract:
This multimedia case should be assigned to students in advance of class. Instructors should consider the timing of making the (B) Case videos available to students, as they may reveal key case details.
Abstract: Florian Hillen, co-founder... View Details
Abstract: Florian Hillen, co-founder... View Details
Keywords: Diagnostics; Organization Design; Change Management; Disruption; Transformation; Health Care and Treatment; AI and Machine Learning; Technology Adoption; Technological Innovation; Management Style; Organizational Culture; Success; Technology Industry; Health Industry; United States
Neeley, Tsedal, Levi Stroud, Ruth Page, and Dave Habeeb. "The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation (A)." Harvard Business School Multimedia/Video Case 425-720, January 2025.
- 22 Feb 2024
- Research & Ideas
How to Make AI 'Forget' All the Private Data It Shouldn't Have
There’s a virtual elephant in AI’s room: It’s nearly impossible to make the technology forget. And there are an increasing number of scenarios where consumers and programmers may not only want to remove data... View Details
- September 2023 (Revised April 2024)
- Case
Atomwise: Strategic Opportunities in AI for Pharma
By: Satish Tadikonda
Abraham Heifets and his co-founder, Izhar Wallach, had founded Atomwise to develop i) an AI engine to transform drug discovery by creating better medicines faster, and ii) a machine learning-based discovery engine that combined the power of convolutional neural... View Details
Keywords: Business Model; Business Startups; AI and Machine Learning; Science-Based Business; Technological Innovation; Biotechnology Industry; Pharmaceutical Industry
Tadikonda, Satish. "Atomwise: Strategic Opportunities in AI for Pharma." Harvard Business School Case 824-043, September 2023. (Revised April 2024.)
- 2024
- Working Paper
The Uneven Impact of Generative AI on Entrepreneurial Performance
By: Nicholas G. Otis, Rowan Clarke, Solène Delecourt, David Holtz and Rembrand Koning
Scalable and low-cost AI assistance has the potential to improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it difficult to know whether recent AI advances can help business owners make... View Details
Keywords: AI and Machine Learning; Performance Improvement; Small Business; Decision Choices and Conditions; Kenya
Otis, Nicholas G., Rowan Clarke, Solène Delecourt, David Holtz, and Rembrand Koning. "The Uneven Impact of Generative AI on Entrepreneurial Performance." Harvard Business School Working Paper, No. 24-042, December 2023.
- 2023
- Working Paper
Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality
By: Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani
The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine... View Details
Keywords: Large Language Model; AI and Machine Learning; Performance Efficiency; Performance Improvement
Dell'Acqua, Fabrizio, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, and Karim R. Lakhani. "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality." Harvard Business School Working Paper, No. 24-013, September 2023.
- 26 Aug 2024
- Research & Ideas
Can AI Match Human Ingenuity in Creative Problem-Solving?
When ChatGPT and other large language models began entering the mainstream two years ago, it quickly became apparent the technology could excel at certain business functions, yet it was less clear how well artificial intelligence could handle more creative tasks. Sure,... 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.)
- May 9, 2023
- Article
8 Questions About Using AI Responsibly, Answered
By: Tsedal Neeley
Generative AI tools are poised to change the way every business operates. As your own organization begins strategizing which to use, and how, operational and ethical considerations are inevitable. This article delves into eight of them, including how your organization... View Details
Neeley, Tsedal. "8 Questions About Using AI Responsibly, Answered." Harvard Business Review (website) (May 9, 2023).
- March 2025 (Revised May 2025)
- Case
Xfund and Sam Altman: Finding Harvard's Best Generative AI Founders
By: Suraj Srinivasan
On May 1, 2024, Xfund Managing Partners Patrick Chung and Brandon Farwell, hosted a high-stakes venture pitch session designed to select one startup for a minimum $100,000 investment. This “Xperiment Stake” competition, dedicated to startups in the Generative AI... View Details
Keywords: AI and Machine Learning; Venture Capital; Innovation Leadership; Technological Innovation; Business Startups; Competition; Technology Industry; United States
Srinivasan, Suraj. "Xfund and Sam Altman: Finding Harvard's Best Generative AI Founders." Harvard Business School Case 125-090, March 2025. (Revised May 2025.)
- 2024
- Article
Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
By: Michael Lingzhi Li and Kosuke Imai
A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today’s scientists across... View Details
Li, Michael Lingzhi, and Kosuke Imai. "Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules." Journal of Causal Inference 12, no. 1 (2024).
- October 2023
- Article
Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
We study how a regulator can best target inspections. Our case study is a U.S. Occupational Safety and Health Administration (OSHA) program that randomly allocated some inspections. On average, each inspection averted 2.4 serious injuries (9%) over the next five years.... View Details
Keywords: Safety Regulations; Regulations; Regulatory Enforcement; Machine Learning Models; Safety; Operations; Service Operations; Production; Forecasting and Prediction; Decisions; United States
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA." American Economic Journal: Applied Economics 15, no. 4 (October 2023): 30–67. (Profiled in the Regulatory Review.)