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  • October 2023 (Revised January 2025)
  • Case

Sydney Loves Kevin

By: Ryan W. Buell and Himabindu Lakkaraju
Kevin Roose was a columnist and podcast host for the New York Times, who focused on technology and its effects on society. When Microsoft launched the latest version of its search engine Bing in February 2023, the company invited Roose to its Redmond campus to... View Details
Keywords: Newspapers; AI and Machine Learning; Technology Adoption; Technological Innovation; Perspective; Media and Broadcasting Industry; Technology Industry
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Buell, Ryan W., and Himabindu Lakkaraju. "Sydney Loves Kevin." Harvard Business School Case 624-039, October 2023. (Revised January 2025.)
  • March 2025
  • Case

Mobvoi's Path Through Market Challenges and Business Reinvention

By: Paul A. Gompers and Shu Lin
Founded in 2012, Mobvoi evolved through multiple transformations—from AI-driven voice technology to smart wearables and later AI-generated content. Backed by major investors, the company navigated shifts in strategy while facing two failed IPO attempts. As market... View Details
Keywords: Business Startups; Entrepreneurship; AI and Machine Learning; Transformation; Initial Public Offering; Business Strategy; Technology Industry; China
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Gompers, Paul A., and Shu Lin. "Mobvoi's Path Through Market Challenges and Business Reinvention." Harvard Business School Case 825-158, March 2025.
  • July 2023
  • Supplement

Honeycomb (B): Jumping on The Generative AI Bandwagon?

By: Jeffrey J. Bussgang and Kumba Sennaar
Honeycomb, an audio app enabling users to record stories and save family memories, considers pivoting to embrace generative AI. What should the co-founders business model look like if they pursued this new direction? View Details
Keywords: Entrepreneurship; Venture Capital; Operations; Business Startups; Business Model; AI and Machine Learning; Technology Industry; United States
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Bussgang, Jeffrey J., and Kumba Sennaar. "Honeycomb (B): Jumping on The Generative AI Bandwagon?" Harvard Business School Supplement 824-013, July 2023.
  • September 2024 (Revised January 2025)
  • Exercise

Building an AI First Snack Company: A Hands-on Generative AI Exercise

By: Iavor I. Bojinov
Although the term 'Generative AI' (GenAI) is widely recognized, its practical application in daily workflows has yet to be understood. This exercise introduces students to GenAI tools, demonstrating how they can be seamlessly integrated into professional work practices... View Details
Keywords: AI and Machine Learning; Technology Adoption; Marketing Strategy; Product Launch; Brands and Branding
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Bojinov, Iavor I. "Building an AI First Snack Company: A Hands-on Generative AI Exercise." Harvard Business School Exercise 625-052, September 2024. (Revised January 2025.)
  • March 2023
  • Teaching Note

VideaHealth: Building the AI Factory

By: Karim R. Lakhani
Teaching Note for HBS Case No. 621-021. The case “VideaHealth: Building the AI Factory” examines the creation of dental startup VideaHealth (Videa) and the development of its artificial intelligence (AI)-led business strategy through the eyes of founder and CEO Florian... View Details
Keywords: AI and Machine Learning; Applications and Software; Business Model; Marketing Strategy; Product Development; Health Industry; Technology Industry
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Lakhani, Karim R. "VideaHealth: Building the AI Factory." Harvard Business School Teaching Note 623-073, March 2023.
  • July 2024
  • Article

How Artificial Intelligence Constrains Human Experience

By: A. Valenzuela, S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino and K. Wertenbroch
Many consumption decisions and experiences are digitally mediated. As a consequence, consumer behavior is increasingly the joint product of human psychology and ubiquitous algorithms (Braun et al. 2024; cf. Melumad et al. 2020). The coming of age of Large Language... View Details
Keywords: Large Language Model; User Experience; AI and Machine Learning; Consumer Behavior; Technology Adoption; Risk and Uncertainty; Cost vs Benefits
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Valenzuela, A., S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino, and K. Wertenbroch. "How Artificial Intelligence Constrains Human Experience." Journal of the Association for Consumer Research 9, no. 3 (July 2024): 241–256.
  • 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.)
  • April 2025
  • Case

Breezm: Innovative 3D-Printed Eyewear (A)

By: Juan Alcácer, Brian Mao Fu and Adina Wong
In 2023, Breezm, a South Korean startup, faced a strategic decision about how to grow its innovative 3D-printed, custom-fit eyewear business. Co-founded in 2017 by Zenma Park and Wooseok Sung, Breezm combined facial scanning, AI, and in-house production to solve the... View Details
Keywords: 3D Printing; Eyeyewear; Growth; Business Startups; AI and Machine Learning; Technological Innovation; Growth and Development Strategy; Risk and Uncertainty; Expansion; South Korea
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Alcácer, Juan, Brian Mao Fu, and Adina Wong. "Breezm: Innovative 3D-Printed Eyewear (A)." Harvard Business School Case 725-376, April 2025.
  • November 2024 (Revised April 2025)
  • Case

Cheerful Music

By: Shunyuan Zhang, Feng Zhu and Nancy Hua Dai
Established by Snow Jiang in 2019 in Shenzhen, China, Cheerful Music was a record label company that had created many hit songs in China. “Yi Xiao Jiang Hu,” its most famous hit song, gained billions of views on social media platforms in China and overseas as the... View Details
Keywords: Generative Ai; Music Entertainment; Global Strategy; Business Model; AI and Machine Learning; Market Entry and Exit; Music Industry; China; United Kingdom; London
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Zhang, Shunyuan, Feng Zhu, and Nancy Hua Dai. "Cheerful Music." Harvard Business School Case 525-031, November 2024. (Revised April 2025.)
  • October 2024 (Revised February 2025)
  • Case

AI and Brand Management: Promises and Perils

By: Julian De Freitas and Elie Ofek
As AI gains traction across industries, companies anticipate that AI will revolutionize both backend processes and customer-facing interactions—with brands eager to leverage AI for tailored marketing materials and automated consumer engagements. Yet, despite a dramatic... View Details
Keywords: AI and Machine Learning; Brands and Branding; Reputation; Technology Adoption; Competitive Advantage
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De Freitas, Julian, and Elie Ofek. "AI and Brand Management: Promises and Perils." Harvard Business School Case 525-021, October 2024. (Revised February 2025.)
  • June 2024 (Revised September 2024)
  • Case

Driving Scale with Otto

By: Rebecca Karp, David Allen and Annelena Lobb
This case asks how startup founders make scaling decisions in light of their priorities for their business and for themselves. Otto was a technology company that applied artificial intelligence technology to sales. It deployed natural language processing to find sales... View Details
Keywords: Artificial Intelligence; Natural Language Processing; B2B; B2B Innovation; Scaling; Scaling Tech Ventures; Business Startups; AI and Machine Learning; Finance; Sales; Business Strategy; Growth and Development Strategy; Entrepreneurship; Information Technology Industry; United States; Cambridge; New York (city, NY); Spain
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Karp, Rebecca, David Allen, and Annelena Lobb. "Driving Scale with Otto." Harvard Business School Case 724-407, June 2024. (Revised September 2024.)
  • June 2020
  • Article

Real-time Data from Mobile Platforms to Evaluate Sustainable Transportation Infrastructure

By: Omar Isaac Asensio, Kevin Alvarez, Arielle Dror, Emerson Wenzel, Catharina Hollauer and Sooji Ha
By displacing gasoline and diesel fuels, electric cars and fleets reduce emissions from the transportation sector, thus offering important public health benefits. However, public confidence in the reliability of charging infrastructure remains a fundamental barrier to... View Details
Keywords: Environmental Sustainability; Transportation; Infrastructure; Behavior; AI and Machine Learning; Demand and Consumers
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Asensio, Omar Isaac, Kevin Alvarez, Arielle Dror, Emerson Wenzel, Catharina Hollauer, and Sooji Ha. "Real-time Data from Mobile Platforms to Evaluate Sustainable Transportation Infrastructure." Nature Sustainability 3, no. 6 (June 2020): 463–471.
  • March 2024 (Revised May 2024)
  • Case

Amperity: First-Party Data at a Crossroads

By: Elie Ofek, Hema Yoganarasimhan and Alexis Lefort
In the summer of 2023, Amperity management was facing a critical decision on its future direction. Given the dramatic changes occurring within the digital advertising ecosystem, as concerns over consumer privacy placed limits on the ability to engage in third-party... View Details
Keywords: AI and Machine Learning; Technology Adoption; Business Strategy; Digital Marketing; Price; Product; Business or Company Management; Advertising Industry
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Ofek, Elie, Hema Yoganarasimhan, and Alexis Lefort. "Amperity: First-Party Data at a Crossroads." Harvard Business School Case 524-017, March 2024. (Revised May 2024.)
  • 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
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De Freitas, Julian, and G. Cohen. "The Health Risks of Generative AI-Based Wellness Apps." Nature Medicine 30, no. 5 (May 2024): 1269–1275.
  • 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, and big data combined with rapid... View Details
Keywords: by James Heskett
  • 2024
  • Working Paper

The Value of AI Innovations

By: Wilbur Xinyuan Chen, Terrence Tianshuo Shi and Suraj Srinivasan
We study the value of AI innovations as it diffuses across general and application sectors, using the United States Patent and Trademark Office’s (USPTO) AI patent dataset. Investors value these innovations more than others, as AI patents exhibit a 9% value premium,... View Details
Keywords: AI and Machine Learning; Valuation; Technological Innovation; Open Source Distribution; Patents; Policy; Knowledge Sharing; Technology Industry
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Chen, Wilbur Xinyuan, Terrence Tianshuo Shi, and Suraj Srinivasan. "The Value of AI Innovations." Harvard Business School Working Paper, No. 24-069, May 2024.
  • 02 Oct 2018
  • First Look

New Research and Ideas, October 2, 2018

policies. Download working paper: https://www.hbs.edu/faculty/Pages/item.aspx?num=55050 "Developing Theory Using Machine Learning Methods By: Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres... View Details
Keywords: Dina Gerdeman
  • July–August 2025
  • Article

Don’t Let an AI Failure Harm Your Brand

By: Julian De Freitas
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
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De Freitas, Julian. "Don’t Let an AI Failure Harm Your Brand." Harvard Business Review 103, no. 4 (July–August 2025): 126–133.
  • 2023
  • Article

Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten

By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details
Keywords: Analytics and Data Science; AI and Machine Learning; Decision Making; Governing Rules, Regulations, and Reforms
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Lakkaraju, Himabindu, Satyapriya Krishna, and Jiaqi Ma. "Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 17808–17826.
  • April 2024 (Revised December 2024)
  • Case

Anthropic: Building Safe AI

By: Shikhar Ghosh and Shweta Bagai
In late 2024, Anthropic, a leading AI safety and research company, achieved a significant breakthrough with computer use capabilities that allowed AI to interact with computers like humans. Co-founded by former OpenAI employees and known for its generative AI... View Details
Keywords: AI and Machine Learning; Corporate Accountability; Corporate Social Responsibility and Impact; Business Growth and Maturation; Corporate Strategy; Technology Industry; United States
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Ghosh, Shikhar, and Shweta Bagai. "Anthropic: Building Safe AI." Harvard Business School Case 824-129, April 2024. (Revised December 2024.)
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