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Show Results For
- All HBS Web
(1,036)
- People (1)
- News (155)
- Research (661)
- Events (13)
- Multimedia (3)
- Faculty Publications (572)
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- June 19, 2023
- Article
Should You Start a Generative AI Company?
Many entrepreneurs are considering starting companies that leverage the latest generative AI technology, but they must ask themselves whether they have what it takes to compete on increasingly commoditized foundational models, or whether they should instead... View Details
De Freitas, Julian. "Should You Start a Generative AI Company?" Harvard Business Review (website) (June 19, 2023).
- July 2025
- Case
The Future in Sight: LumineticsCore and the First Autonomous AI for Diagnostics
By: Michael Lingzhi Li and Tinglong Dai
After two decades of research, Dr. Michael Abramoff successfully launched LumineticsCore—the first autonomous AI system authorized by the FDA to diagnose diabetic retinopathy without physician oversight. The case traces his journey across algorithm design, clinical... View Details
- Article
AI Companions Reduce Loneliness
By: Julian De Freitas, Zeliha Oğuz-Uğuralp, Ahmet K. Uğuralp and Stefano Puntoni
Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications are... View Details
De Freitas, Julian, Zeliha Oğuz-Uğuralp, Ahmet K. Uğuralp, and Stefano Puntoni. "AI Companions Reduce Loneliness." Journal of Consumer Research (in press). (Pre-published online June 25, 2025.)
- 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).
- 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.)
- Working Paper
AI in Disguise—How AI-generated Ads' Visual Cues Shape Consumer Perception and Performance
By: Yannick Exner, Jochen Hartmann, Oded Netzer and Shunyuan Zhang
Generative AI’s recent advancements in creating content have offered vast potential to transform the advertising industry. This research investigates the impact of generative AI-enabled visual ad creation on real-world advertising effectiveness. For this purpose, we... View Details
Keywords: Digital Marketing; AI and Machine Learning; Advertising; Consumer Behavior; Advertising Industry
Exner, Yannick, Jochen Hartmann, Oded Netzer, and Shunyuan Zhang. "AI in Disguise—How AI-generated Ads' Visual Cues Shape Consumer Perception and Performance." SSRN Working Paper Series, No. 5096969.
- May 2020
- Case
Numenta in 2020: The Future of AI
By: David B. Yoffie, Cameron Armstrong, Mei Tao and Marta Zwierz
In 2020, Numenta’s co-founder, Jeff Hawkins, completed his pathbreaking research on artificial intelligence. His co-founder and CEO, Donna Dubinsky, had to find a business model to monetize the technology. This case explores the challenges of building a business... View Details
Keywords: Artificial Intelligence; Monetization; Information Technology; Strategy; Intellectual Property; Business Model; AI and Machine Learning; Technology Industry
Yoffie, David B., Cameron Armstrong, Mei Tao, and Marta Zwierz. "Numenta in 2020: The Future of AI." Harvard Business School Case 720-463, May 2020.
- June 2025
- Article
Unregulated Emotional Risks of AI Wellness Apps
By: Julian De Freitas and Glenn Cohen
We propose that AI-driven wellness apps powered by large language models can foster extreme emotional attachments and dependencies akin to human relationships—posing risks like ambiguous loss and dysfunctional dependence—that challenge current regulatory frameworks and... View Details
De Freitas, Julian, and Glenn Cohen. "Unregulated Emotional Risks of AI Wellness Apps." Nature Machine Intelligence 7, no. 6 (June 2025): 813–815.
- Forthcoming
- Article
Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation
By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
Even if algorithms make better predictions than humans on average, humans may sometimes have private information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by... View Details
Keywords: AI and Machine Learning; Analytics and Data Science; Forecasting and Prediction; Digital Marketing
Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation." Management Science (forthcoming). (Pre-published online March 24, 2025.)
- July–August 2024
- Article
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to... View Details
Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.
- June 2017
- Teaching Note
IBM Transforming, 2012–2016: Ginni Rometty Steers Watson
By: Rosabeth Moss Kanter and Jonathan Cohen
Ginni Rometty, who became IBM CEO in 2012, led efforts to transform the company around cognitive computing and the AI platform Watson. This Teaching Note helps instructors understand and teach the Harvard Business School case “IBM Transforming, 2012–2016: Ginni Rometty... View Details
- 2023
- Working Paper
Black-box Training Data Identification in GANs via Detector Networks
By: Lukman Olagoke, Salil Vadhan and Seth Neel
Since their inception Generative Adversarial Networks (GANs) have been popular generative models across images, audio, video, and tabular data. In this paper we study whether given access to a trained GAN, as well as fresh samples from the underlying distribution, if... View Details
Olagoke, Lukman, Salil Vadhan, and Seth Neel. "Black-box Training Data Identification in GANs via Detector Networks." Working Paper, October 2023.
- July–August 2021
- Article
Why You Aren't Getting More from Your Marketing AI
By: Eva Ascarza, Michael Ross and Bruce G.S. Hardie
Fewer than 40% of companies that invest in AI see gains from it, usually because of one or more of these errors: (1) They don’t ask the right question, and end up directing AI to solve the wrong problem. (2) They don’t recognize the differences between the value of... View Details
Keywords: Artificial Intelligence; Marketing; Decision Making; Communication; Framework; AI and Machine Learning
Ascarza, Eva, Michael Ross, and Bruce G.S. Hardie. "Why You Aren't Getting More from Your Marketing AI." Harvard Business Review 99, no. 4 (July–August 2021): 48–54.
- January 2025
- Case
Moderna: Democratizing Artificial Intelligence
By: Iavor I. Bojinov, Karim R. Lakhani, Annika Hildebrandt and James Weber
The case study examines Moderna's journey in democratizing artificial intelligence (AI), particularly generative AI, across its workforce. It details the company's "digital-first, AI-focused" approach, including the rollout of OpenAI's ChatGPT Enterprise to all... View Details
Keywords: AI and Machine Learning; Technology Adoption; Innovation Strategy; Governance Controls; Biotechnology Industry
Bojinov, Iavor I., Karim R. Lakhani, Annika Hildebrandt, and James Weber. "Moderna: Democratizing Artificial Intelligence." Harvard Business School Case 625-070, January 2025.
- May–June 2024
- Article
Should Your Brand Hire a Virtual Influencer?
By: Serim Hwang, Shunyuan Zhang, Xiao Liu and Kannan Srinivasan
Followers respond more favorably to sponsored posts by virtual influencers versus those by humans, costs are lower, and creating an influencer from scratch allows marketers to introduce more diversity. View Details
Hwang, Serim, Shunyuan Zhang, Xiao Liu, and Kannan Srinivasan. "Should Your Brand Hire a Virtual Influencer?" Harvard Business Review 102, no. 3 (May–June 2024): 56–60.
- February 2025
- Case
K Health: Building an AI Physician Model
By: Iavor I. Bojinov, Karim R. Lakhani, Sarah Sasso and Carin-Isabel Knoop
Allon Bloch, CEO and cofounder of K Health, encountered a number of challenges and opportunities to navigate as the company prepared to launch its AI-driven healthcare platform in the U.S. in 2018. The case examines the potential of artificial intelligence to improve... View Details
Keywords: Health Care and Treatment; AI and Machine Learning; Product Launch; Business Strategy; Technology Industry; Health Industry; United States
Bojinov, Iavor I., Karim R. Lakhani, Sarah Sasso, and Carin-Isabel Knoop. "K Health: Building an AI Physician Model." Harvard Business School Case 625-079, February 2025.
- January 2024 (Revised February 2024)
- Case
OpenAI: Idealism Meets Capitalism
By: Shikhar Ghosh and Shweta Bagai
In November 2023, the board of OpenAI, one of the most successful companies in the history of technology, decided to fire Sam Altman, its charismatic and influential CEO. Their decision shocked the corporate world and had people wondering why OpenAI had designed a... View Details
Keywords: AI; AI and Machine Learning; Governing and Advisory Boards; Ethics; Strategy; Technological Innovation; Leadership
Ghosh, Shikhar, and Shweta Bagai. "OpenAI: Idealism Meets Capitalism." Harvard Business School Case 824-134, January 2024. (Revised February 2024.)
- March–April 2025
- Article
Strategy in an Era of Abundant Expertise: How to Thrive When AI Makes Knowledge and Know-How Cheaper and Easier to Access
By: Bobby Yerramilli-Rao, John Corwin, Yang Li and Karim R. Lakhani
The AI era is in its early stages, and the technology is evolving extremely quickly. Providers are rapidly introducing AI "copilots," "bots," and "assistants" into applications to augment employees' workflows. Examples include GitHub Copilot for coding, ServiceNow... View Details
Keywords: AI; AI and Machine Learning; Performance Productivity; Experience and Expertise; Technology Adoption
Yerramilli-Rao, Bobby, John Corwin, Yang Li, and Karim R. Lakhani. "Strategy in an Era of Abundant Expertise: How to Thrive When AI Makes Knowledge and Know-How Cheaper and Easier to Access." Harvard Business Review 103, no. 2 (March–April 2025): 72–81.
- 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
De Freitas, Julian, and G. Cohen. "The Health Risks of Generative AI-Based Wellness Apps." Nature Medicine 30, no. 5 (May 2024): 1269–1275.
- 2025
- Article
Humor as a Window into Generative AI Bias
By: Roger Samure, Julian De Freitas and Stefano Puntoni
A preregistered audit of 600 images by generative AI across 150 different prompts explores the link between humor and discrimination in consumer-facing AI solutions. When ChatGPT updates images to make them “funnier”, the prevalence of stereotyped groups changes. While... View Details
Samure, Roger, Julian De Freitas, and Stefano Puntoni. "Humor as a Window into Generative AI Bias." Art. 1326. Scientific Reports 15 (2025).