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  • All HBS Web  (670)
    • News  (183)
    • Research  (381)
    • Events  (6)
    • Multimedia  (13)
  • Faculty Publications  (283)

Show Results For

  • All HBS Web  (670)
    • News  (183)
    • Research  (381)
    • Events  (6)
    • Multimedia  (13)
  • Faculty Publications  (283)
← Page 7 of 670 Results →
  • August 2023
  • Case

Kariyer.net: Recruiting AI

By: Shunyuan Zhang, Fares Khrais and Namrata Arora
In 2017, Fatih Uysal (AMP 2021) became CEO of Kariyer.net. By then, the business was already the industry leading online job board in Turkey. However, faced with stalling growth, a turbulent macroenvironment, and growing competition from international players, Uysal... View Details
Keywords: Online Technology; Marketing; Websites; Artificial Intelligence; Innovation; Two-sided Platforms; Internet and the Web; Product Launch; Product Positioning; Job Search; Employment; Transformation; Volatility; Innovation and Invention; Disruptive Innovation; Management Practices and Processes; Business Growth and Maturation; Competitive Strategy; Business Startups; Talent and Talent Management; Cost vs Benefits; Macroeconomics; Corporate Entrepreneurship; Emerging Markets; Digital Platforms; Employment Industry; Information Technology Industry; Technology Industry; Middle East; Turkey
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Zhang, Shunyuan, Fares Khrais, and Namrata Arora. "Kariyer.net: Recruiting AI." Harvard Business School Case 524-014, August 2023.
  • 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
Keywords: Monetization Strategy; Artificial Intelligence; Forecasting and Prediction; Applications and Software; Technological Innovation; Marketing; Segmentation; AI and Machine Learning; Construction Industry; Turkey
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Mojir, Navid. "Borusan CAT: Monetizing Prediction in the Age of AI." Harvard Business School Teaching Note 522-069, February 2022.
  • 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
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Kumar, Ram Shankar Siva, and Frank Nagle. "The Case for AI Insurance." Harvard Business Review Digital Articles (April 29, 2020).
  • 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... View Details
Keywords: fintech; Artificial intelligence; Small business
  • Article

Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting

By: Raymond H. Mak, Michael G. Endres, Jin Hyun Paik, Rinat A. Sergeev, Hugo Aerts, Christopher L. Williams, Karim R. Lakhani and Eva C. Guinan
Importance: Radiation therapy (RT) is a critical cancer treatment, but the existing radiation oncologist work force does not meet growing global demand. One key physician task in RT planning involves tumor segmentation for targeting, which requires substantial... View Details
Keywords: Crowdsourcing; AI Algorithms; Health Care and Treatment; Collaborative Innovation and Invention; AI and Machine Learning
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Mak, Raymond H., Michael G. Endres, Jin Hyun Paik, Rinat A. Sergeev, Hugo Aerts, Christopher L. Williams, Karim R. Lakhani, and Eva C. Guinan. "Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting." JAMA Oncology 5, no. 5 (May 2019): 654–661.
  • 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
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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.)
  • 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).
  • 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
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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 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
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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).
  • 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
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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
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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.
  • May 2017 (Revised March 2018)
  • Case

Predicting Consumer Tastes with Big Data at Gap

By: Ayelet Israeli and Jill Avery
CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big... View Details
Keywords: Retailing; Preference Elicitation; Big Data; Predictive Analytics; Artificial Intelligence; Fashion; Marketing; Marketing Strategy; Marketing Channels; Brands and Branding; Consumer Behavior; Demand and Consumers; Analytics and Data Science; Forecasting and Prediction; E-commerce; Apparel and Accessories Industry; Consumer Products Industry; Fashion Industry; Retail Industry; United States; Canada; North America
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Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Case 517-115, May 2017. (Revised March 2018.)
  • 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
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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.
  • Research Summary

Overview

By: Roberto Verganti
Roberto’s research focuses on how to create innovations that are meaningful for people, for society, and for their creators. He explores how leaders and organizations generate radically new visions, and make those visions come real. His studies lie at the intersection... View Details
Keywords: Integrated Design; Strategy; Design Thinking; Innovation; Artificial Intelligence; Design; Technology; Leadership; Innovation Strategy
  • December 2020
  • Case

VIA Science (A)

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; Markets; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan
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Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (A)." Harvard Business School Case 721-367, December 2020.
  • June 2025
  • Supplement

Transforming a Titan (B)

By: George Serafeim and Lena Duchene
After a global search the board appoints Marcel Cobuz—ex-LafargeHolcim executive with deep innovation experience—as TITAN’s first non-family CEO. Cobuz co-creates a four-pillar roadmap: sharpen the core cement portfolio, accelerate low-carbon products and aggregates,... View Details
Keywords: AI; Artificial Intelligence; CEO Succession; CEO Role; Family Business
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Serafeim, George, and Lena Duchene. "Transforming a Titan (B)." Harvard Business School Supplement 125-122, June 2025.
  • January 2018 (Revised March 2019)
  • Case

Autonomous Vehicles: The Rubber Hits the Road...but When?

By: William Kerr, Allison Ciechanover, Jeff Huizinga and James Palano
The rise of autonomous vehicles has enormous implications for business and society. Despite the many headlines and significant investment in the technology by early 2019, it was still unclear when truly autonomous vehicles would be a commercial reality. Students will... View Details
Keywords: Technology Management; Artificial Intelligence; General Management; Robotics; Technological Innovation; Transportation; Disruption; Information Technology; Decision Making; AI and Machine Learning; Auto Industry; Technology Industry
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Kerr, William, Allison Ciechanover, Jeff Huizinga, and James Palano. "Autonomous Vehicles: The Rubber Hits the Road...but When?" Harvard Business School Case 818-088, January 2018. (Revised March 2019.)
  • 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
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Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (B)." Harvard Business School Supplement 721-368, December 2020.
  • 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
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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.)
  • July 2019 (Revised November 2019)
  • Case

Osaro: Picking the Best Path

By: William R. Kerr, James Palano and Bastiane Huang
The founder of Osaro saw the potential of deep reinforcement learning to allow robots to be applied to new applications. Osaro targeted warehousing, already a dynamic industry for robotics and automation, for its initial product—a system which would allow robotic arms... View Details
Keywords: Artificial Intelligence; Machine Learning; Robotics; Robots; Ecommerce; Fulfillment; Warehousing; AI; Startup; Technology Commercialization; Business Startups; Entrepreneurship; Logistics; Order Taking and Fulfillment; Information Technology; Commercialization; Learning; Complexity; Competition; E-commerce
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Kerr, William R., James Palano, and Bastiane Huang. "Osaro: Picking the Best Path." Harvard Business School Case 820-012, July 2019. (Revised November 2019.)
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