Filter Results
:
(1,260)
Show Results For
-
All HBS Web
(1,260)
- People (4)
- News (416)
- Research (595)
- Events (9)
- Multimedia (20)
- Faculty Publications (390)
Show Results For
-
All HBS Web
(1,260)
- People (4)
- News (416)
- Research (595)
- Events (9)
- Multimedia (20)
- Faculty Publications (390)
- 23 Oct 2020
- News
Now Is the Time to Shake Up Your Sales Processes
- 01 Sep 2020
- News
Elevator Pitch: First Byte
Illustration by Drue Wagner Illustration by Drue Wagner Concept: “Alfred,” a food industry collaborative robot, or “cobot,” trained to assist in the assembly of items such as salads and food bowls at commercial kitchens and fast-casual restaurants. Through AI, Alfred...
View Details
- April 2021 (Revised August 2021)
- Case
Borusan CAT: Monetizing Prediction in the Age of AI (A)
By: Navid Mojir and Gamze Yucaoglu
Borusan Cat is an international distributor of Caterpillar heavy machines. Esra Durgun (Director of Strategy, Digitization, and Innovation) and Ozgur Gunaydin (CEO) seem to have bet their careers on developing Muneccim, a new predictive technology that is designed to...
View Details
Keywords:
Monetization Strategy;
Artificial Intelligence;
AI;
Forecasting and Prediction;
Applications and Software;
Technological Innovation;
Marketing;
Segmentation;
AI and Machine Learning;
Construction Industry;
Turkey
Mojir, Navid, and Gamze Yucaoglu. "Borusan CAT: Monetizing Prediction in the Age of AI (A)." Harvard Business School Case 521-053, April 2021. (Revised August 2021.)
- 01 Mar 2003
- News
Visionary of the Year
HBS professor Rosabeth Moss Kanter was named the Intelligent Community Visionary of the Year in 2002 by the Intelligent Community Forum. The award recognizes an individual or group that has taken a...
View Details
- February 2022
- Teaching Note
Borusan CAT: Monetizing Prediction in the Age of AI
By: Navid Mojir
Teaching Note for HBS Case No. 521-053.
View Details
- April 29, 2020
- Article
The Case for AI Insurance
By: Ram Shankar Siva Kumar and Frank Nagle
When organizations place machine learning systems at the center of their businesses, they introduce the risk of failures that could lead to a data breach, brand damage, property damage, business interruption, and in some cases, bodily harm. Even when companies are...
View Details
Keywords:
Artificial Intelligence;
Machine Learning;
Internet and the Web;
Safety;
Insurance;
AI and Machine Learning;
Cybersecurity
Kumar, Ram Shankar Siva, and Frank Nagle. "The Case for AI Insurance." Harvard Business Review Digital Articles (April 29, 2020).
- 12 Jun 2014
- News
Why Smart People Struggle with Strategy
- 26 Nov 2019
- News
Fintech, Small Business & the American Dream
is highlighted in her new book: Fintech, Small Business & the American Dream. KEY THEMES Small business is critical to the American economy. Artificial intelligence and big data will transform financial services, particularly small...
View Details
- March 2022
- Article
Winner Takes All? Tech Clusters, Population Centers, and the Spatial Transformation of U.S. Invention
By: Brad Chattergoon and William R. Kerr
U.S. invention has become increasingly concentrated around major tech centers since the 1970s, with implications for how much cities across the country share in concomitant local benefits. Is invention becoming a winner-takes-all race? We explore the rising spatial...
View Details
Keywords:
Clusters;
Invention;
Agglomeration;
Artificial Intelligence;
Innovation and Invention;
Patents;
Applications and Software;
Industry Clusters;
AI and Machine Learning
Chattergoon, Brad, and William R. Kerr. "Winner Takes All? Tech Clusters, Population Centers, and the Spatial Transformation of U.S. Invention." Art. 104418. Research Policy 51, no. 2 (March 2022).
- 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).
- 2021
- Working Paper
Winner Takes All? Tech Clusters, Population Centers, and the Spatial Transformation of U.S. Invention
By: Brad Chattergoon and William R. Kerr
U.S. invention has become increasingly concentrated around major tech centers since the 1970s, with implications for how much cities across the country share in concomitant local benefits. Is invention becoming a winner-takes-all race? We explore the rising spatial...
View Details
Keywords:
Invention;
Innovation;
Artificial Intelligence;
Clusters;
Agglomeration;
Innovation and Invention;
Patents;
Applications and Software;
Industry Clusters;
United States
Chattergoon, Brad, and William R. Kerr. "Winner Takes All? Tech Clusters, Population Centers, and the Spatial Transformation of U.S. Invention." Harvard Business School Working Paper, No. 22-027, October 2021. (NBER Working Paper Series, No. 29456, November 2021.)
- March–April 2021
- Article
Network-biased Technical Change: How Information Management Tools Overcome Some Biases but Exacerbate Others.
By: Gerald C. Kane and Lynn Wu
Organizations have long sought to improve employee performance by managing knowledge more effectively. In this paper, we test whether the adoption of digital tools for expertise search and access within an organization, often referred to as a support to an...
View Details
Keywords:
Digital Tools;
Social Media;
Social Networks;
Transactive Memory Systems;
Augmented Intelligence;
Artificial Intelligence;
Social and Collaborative Networks;
Gender;
Equality and Inequality;
Technology Adoption;
Knowledge Management;
Performance Improvement;
Power and Influence;
Organizational Change and Adaptation
Kane, Gerald C., and Lynn Wu. "Network-biased Technical Change: How Information Management Tools Overcome Some Biases but Exacerbate Others." Organization Science 32, no. 2 (March–April 2021): 273–292.
- 2022
- Book
The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI
By: Paul Leonardi and Tsedal Neeley
The pressure to "be digital" has never been greater, but you can meet the challenge.
The digital revolution is here, changing how work gets done, how industries are structured, and how people from all walks of life work, behave, and relate to each other. To thrive...
View Details
Keywords:
Digital;
Artificial Intelligence;
Big Data;
Digital Transformation;
Technological Innovation;
Transformation;
Learning;
Competency and Skills
Leonardi, Paul, and Tsedal Neeley. The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI. Boston, MA: Harvard Business Review Press, 2022.
- February 2022 (Revised November 2022)
- Case
Nuritas
By: Mitchell Weiss, Satish Tadikonda, Vincent Dessain and Emer Moloney
Nora Khaldi had built a technology “to unlock the power of nature” in the service of extending human lifespan and improving health, and now in April 2020 was debating telling her Board of Directors she wanted to put on ice some of her discoveries. Nuritas, the company...
View Details
Keywords:
Cash Burn;
Cash Flow Analysis;
Pharmaceutical Companies;
Founder;
Artificial Intelligence;
AI;
Entrepreneurship;
Health Testing and Trials;
Health Care and Treatment;
Decision Making;
Market Entry and Exit;
AI and Machine Learning;
Pharmaceutical Industry
Weiss, Mitchell, Satish Tadikonda, Vincent Dessain, and Emer Moloney. "Nuritas." Harvard Business School Case 822-080, February 2022. (Revised November 2022.)
- October 2019
- Article
Making Sense of Recommendations
By: Michael Yeomans, Anuj Shah, Sendhil Mullainathan and Jon Kleinberg
Computer algorithms are increasingly being used to predict people's preferences and make recommendations. Although people frequently encounter these algorithms because they are cheap to scale, we do not know how they compare to human judgment. Here, we compare computer...
View Details
Keywords:
Recommender Systems;
Artificial Intelligence;
Interpretability;
Information Technology;
Forecasting and Prediction;
Decision Making;
Attitudes
Yeomans, Michael, Anuj Shah, Sendhil Mullainathan, and Jon Kleinberg. "Making Sense of Recommendations." Journal of Behavioral Decision Making 32, no. 4 (October 2019): 403–414.
- January 2024 (Revised February 2024)
- Case
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
The case examines Levi Strauss’ journey in implementing machine learning and AI into its financial forecasting process. The apparel company partnered with the IT company Wipro in 2017 to develop a machine learning algorithm that could help Levi Strauss forecast its...
View Details
Keywords:
Investor Relations;
Forecasting;
Machine Learning;
Artificial Intelligence;
Apparel;
Corporate Finance;
Forecasting and Prediction;
AI and Machine Learning;
Digital Transformation;
Apparel and Accessories Industry;
United States
Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Case 224-029, January 2024. (Revised February 2024.)
- 2000
- Book
Learning in Action: A Guide to Putting the Learning Organization to Work
By: David A. Garvin
Keywords:
Market Intelligence;
Learning Organizations;
After-Action Reviews;
Experimentation;
Learning
Garvin, David A. Learning in Action: A Guide to Putting the Learning Organization to Work. Boston: Harvard Business School Press, 2000.
- February 2022 (Revised February 2023)
- Case
TikTok in 2020: Super App or Supernova? (Abridged)
By: Jeffrey F. Rayport, Dan Maher and Dan O'Brien
TikTok’s parent company, ByteDance, was launched in 2012 around a simple idea—helping users entertain themselves on their smartphones while on the Beijing Subway. In less than a decade, it had become one of the world’s most valuable private companies, with investors...
View Details
Keywords:
Digital Platform;
Artificial Intelligence;
AI;
Mobile App;
Mobile App Industry;
Mobile and Wireless Technology;
Market Entry and Exit;
Brands and Branding;
Growth and Development Strategy;
China
Rayport, Jeffrey F., Dan Maher, and Dan O'Brien. "TikTok in 2020: Super App or Supernova? (Abridged)." Harvard Business School Case 822-112, February 2022. (Revised February 2023.)
- 26 Apr 2020
- Other Presentation
Towards Modeling the Variability of Human Attention
By: Kuno Kim, Megumi Sano, Julian De Freitas, Daniel Yamins and Nick Haber
Children exhibit extraordinary exploratory behaviors hypothesized to contribute to the building of models of their world. Harnessing this capacity in artificial systems promises not only more flexible technology but also cognitive models of the developmental processes...
View Details
Keywords:
Exploratory Learning Behaviors;
Modeling;
Artificial Intelligence;
AI and Machine Learning
Kim, Kuno, Megumi Sano, Julian De Freitas, Daniel Yamins, and Nick Haber. "Towards Modeling the Variability of Human Attention." In Bridging AI and Cognitive Science (BAICS) Workshop. 8th International Conference on Learning Representations (ICLR), April 26, 2020.
- December 2020
- Supplement
VIA Science (B)
By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the...
View Details
Keywords:
Data Analytics;
Machine Learning;
Artificial Intelligence;
Strategy;
Business Startups;
AI and Machine Learning;
Telecommunications Industry;
Utilities Industry;
United States;
Japan
Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (B)." Harvard Business School Supplement 721-368, December 2020.