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Show Results For
- All HBS Web
(1,543)
- People (1)
- News (274)
- Research (936)
- Events (19)
- Multimedia (6)
- Faculty Publications (771)
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- 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.
- September–October 2024
- Article
The Crowdless Future? Generative AI and Creative Problem-Solving
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
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.
- 05 Mar 2019
- First Look
New Research and Ideas, March 5, 2019
of behaviors collected at acquisition as well as future propensities to buy and to respond to marketing actions. Using probabilistic machine learning, we combine deep exponential families with the demand... View Details
Keywords: Dina Gerdeman
- 11 Mar 2001
- Research & Ideas
Merchants to Multinationals: British Trading Companies in the Nineteenth and Twentieth Centuries
being a modest market for British textiles into an expanding market not only for textiles, but for British iron and steel, machinery and coal. 1 However the transport View Details
Keywords: by Geoffrey Jones
- 21 Aug 2018
- First Look
New Research and Ideas, August 21, 2018
2018 Boston: Harvard Business Review Press Driving Digital Strategy: A Guide to Reimagining Your Business By: Gupta, Sunil Abstract—Disruption and transformation get a lot of hype and for good reason.... View Details
Keywords: Dina Gerdeman
- 2024
- Working Paper
The Wade Test: Generative AI and CEO Communication
By: Prithwiraj Choudhury, Bart S. Vanneste and Amirhossein Zohrehvand
Can generative artificial intelligence (AI) transform the role of the CEO by effectively automating CEO
communication? This study investigates whether AI can mimic a human CEO and whether employees’
perception of the communication’s source matter. In a field... View Details
Choudhury, Prithwiraj, Bart S. Vanneste, and Amirhossein Zohrehvand. "The Wade Test: Generative AI and CEO Communication." Harvard Business School Working Paper, No. 25-008, August 2024.
- 25 May 2016
- Research & Ideas
How Consumers and Businesses are Reshaping Public Health
savings. In the area of prevention, the spread of ever-cheaper mobile smart phones enables citizens in remote rural areas to receive online medical consultations, treatment suggestions, and prescriptions. Readings on diagnostic View Details
- 11 Apr 2023
- Research & Ideas
Is Amazon a Retailer, a Tech Firm, or a Media Company? How AI Can Help Investors Decide
industry lines as companies increasingly bring seemingly unrelated business lines together in unconventional ways. New research by Awada, Harvard Business School Professor Suraj Srinivasan, and doctoral student Paul J. Hamilton harnesses... 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
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.)
- 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).
- August 1997 (Revised June 2023)
- Case
Fabritek, 1992
Describes a large-volume automotive parts contract in a high-quality machine work company. Quality and delivery problems arise when one of the four men on the job is replaced with a high producer who cannot earn a substantial bonus because of machine interference. View Details
Keywords: Machinery and Machining; Compensation and Benefits; Selection and Staffing; Production; Quality; Manufacturing Industry
Hammond, Janice H. "Fabritek, 1992." Harvard Business School Case 698-014, August 1997. (Revised June 2023.)
- Research Summary
Fintech, Small Business & the American Dream: How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity
By: Karen Mills
Fintech, Small Business & the American Dream describes the needs of small businesses for capital and demonstrates how technology—novel data sources, artificial intelligence, machine learning—will transform the small business lending market. This market has been... View Details
- 2024
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift
By: Matthew DosSantos DiSorbo and Kris Ferreira
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). These outliers often originate from covariate shift,... View Details
DosSantos DiSorbo, Matthew, and Kris Ferreira. "Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift." Working Paper, February 2024.
- January 1995 (Revised October 1995)
- Case
Schweizerische Maschinenfabrik Zug, A.G.
Schweizerische Maschinenfabrik Zug (SMZ), a 110-year old Swiss machinery firm, faces several issues at the end of 1992. It's not clear whether the company will be able to maintain its traditional price premium in the face of foreign competition. The firm must chart a... View Details
Keywords: Competition; Machinery and Machining; Globalized Markets and Industries; Manufacturing Industry; Switzerland
Enright, Michael J. "Schweizerische Maschinenfabrik Zug, A.G." Harvard Business School Case 795-026, January 1995. (Revised October 1995.)
- 12 Apr 2022
- Research & Ideas
Swiping Right: How Data Helped This Online Dating Site Make More Matches
some estimates, with players such as Bumble, Tinder, and OKCupid vying to help people find love. While McFowland is not a dating expert, his work in machine learning and social... View Details
Keywords: by Kara Baskin
- January–February 2023
- Article
Forecasting COVID-19 and Analyzing the Effect of Government Interventions
By: Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis and Dimitris Bertsimas
We developed DELPHI, a novel epidemiological model for predicting detected cases and deaths in the prevaccination era of the COVID-19 pandemic. The model allows for underdetection of infections and effects of government interventions. We have applied DELPHI across more... View Details
Keywords: COVID-19 Pandemic; Epidemics; Analytics and Data Science; Health Pandemics; AI and Machine Learning; Forecasting and Prediction
Li, Michael Lingzhi, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis, and Dimitris Bertsimas. "Forecasting COVID-19 and Analyzing the Effect of Government Interventions." Operations Research 71, no. 1 (January–February 2023): 184–201.
- February 2025
- Article
Disclosure, Humanizing, and Contextual Vulnerability of Generative AI Chatbots
By: Julian De Freitas and I. Glenn Cohen
In the wake of recent advancements in generative AI, regulatory bodies are trying to keep pace. One key decision is whether to require app makers to disclose the use of generative AI-powered chatbots in their products. We suggest that some generative AI-based chatbots... View Details
Keywords: AI and Machine Learning; Governing Rules, Regulations, and Reforms; Applications and Software; Well-being
De Freitas, Julian, and I. Glenn Cohen. "Disclosure, Humanizing, and Contextual Vulnerability of Generative AI Chatbots." New England Journal of Medicine AI 2, no. 2 (February 2025).
- 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
- 26 Jul 2022
- Research & Ideas
Burgers with Bugs? What Happens When Restaurants Ignore Online Reviews
reviews helps consumers choose cleaner restaurants, which is a pretty robust finding." Harvard Business School Assistant Professor Chiara Farronato and Georgios Zervas, an associate professor at Boston University, used View Details
- 11 Feb 2020
- Sharpening Your Skills
10 Rules Entrepreneurs Need to Know Before Adopting AI
Although adoption of artificial intelligence (AI) and machine learning (ML) for the enterprise is still in the early days, the technology has matured enough for entrepreneurs to start gathering inspiration... View Details
Keywords: by Rocio Wu