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  • Research Summary

Overview

Michael is interested in research at the intersection of technology and supply chain in corporations, especially retailers. His recent projects have focused on Human-AI collaboration at retailers. View Details
Keywords: Supply Chain Management; Supply Chain; Operations; AI and Machine Learning; Retail Industry
  • 2025
  • Working Paper

Why Most Resist AI Companions

By: Julian De Freitas, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp and Stefano Puntoni
AI companion applications—designed to serve as synthetic interaction partners—have recently become capable enough to reduce loneliness, a growing public health concern. However, behavioral research has yet to fully explain the barriers to adoption of such AI and... View Details
Keywords: Generative Ai; Chatbots; Artificial Intelligence; Algorithmic Aversion; Lonelines; Technology Adoption; AI and Machine Learning; Well-being; Emotions
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De Freitas, Julian, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp, and Stefano Puntoni. "Why Most Resist AI Companions." Harvard Business School Working Paper, No. 25-030, December 2024. (Revised May 2025.)
  • June 19, 2023
  • Article

Should You Start a Generative AI Company?

By: Julian De Freitas
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
Keywords: Business Startups; Entrepreneurship; AI and Machine Learning; Applications and Software
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De Freitas, Julian. "Should You Start a Generative AI Company?" Harvard Business Review (website) (June 19, 2023).
  • 11 Oct 2024
  • Research & Ideas

How AI Could Ease the Refugee Crisis and Bring New Talent to Businesses

says. “What we’re asking is, can we build algorithms that will help find better matches that will allow people to integrate more easily?” The paper presents data from Switzerland and the United States that showed promise in using machine... View Details
Keywords: by Ben Rand; Technology; Information Technology
  • 2025
  • Working Paper

Generative AI Use by Capital Market Information Intermediaries: Evidence from Seeking Alpha

By: Mark Bradshaw, Chenyang Ma, Benjamin Yost and Yuan Zou
We study the use of generative AI for firm-specific financial analysis on the Seeking Alpha platform. We find that, after the initial launch of ChatGPT in November 2022, the share of AI-generated articles rose sharply to 13.4% of all articles, then declined in late... View Details
Keywords: Generative Ai; Seeking Alpha; Equity Research; Large Language Models; Gpt; AI and Machine Learning; Information Publishing; Financial Markets
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Bradshaw, Mark, Chenyang Ma, Benjamin Yost, and Yuan Zou. "Generative AI Use by Capital Market Information Intermediaries: Evidence from Seeking Alpha." Harvard Business School Working Paper, No. 25-055, April 2025.
  • August 2022 (Revised January 2023)
  • Case

Icario Health: AI to Drive Health Engagement

By: David C. Edelman
Icario Health has built a market-leading artificial intelligence (AI) engine to help health insurers drive better health behaviors for their members, enabling the insurers to improve their Medicare performance. View Details
Keywords: Marketing; Health Care and Treatment; AI and Machine Learning; Health Industry; United States
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Edelman, David C. "Icario Health: AI to Drive Health Engagement." Harvard Business School Case 523-025, August 2022. (Revised January 2023.)
  • September–October 2024
  • Article

The Crowdless Future? Generative AI and Creative Problem-Solving

By: Léonard Boussioux, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic and Karim R. Lakhani
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
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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.
  • October 14, 2023
  • Article

Will Consumers Buy Selfish Self-Driving Cars?

By: Julian De Freitas
Keywords: AI and Machine Learning; Ethics; Technological Innovation; Safety; Auto Industry
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De Freitas, Julian. "Will Consumers Buy Selfish Self-Driving Cars?" Wall Street Journal (October 14, 2023), C5.
  • 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
Keywords: AI and Machine Learning; Well-being; Emotions; Applications and Software
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De Freitas, Julian, Zeliha Oğuz-Uğuralp, Ahmet K. Uğuralp, and Stefano Puntoni. "AI Companions Reduce Loneliness." Journal of Consumer Research (in press).
  • 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
Keywords: AI and Machine Learning; Organizational Change and Adaptation; Prejudice and Bias; Ethics
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Neeley, Tsedal. "8 Questions About Using AI Responsibly, Answered." Harvard Business Review (website) (May 9, 2023).
  • 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
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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.
  • March 27, 2025
  • Article

How One Company Used AI to Broaden Its Customer Base

By: Sunil Gupta and Frank V. Cespedes
The software company SAP successfully leveraged AI tools to begin selling to the small and medium enterprises (SMEs) market, which had previously been uneconomical for its in-person sales approach. By mapping the customer journey and deploying over 40 AI tools, SAP... View Details
Keywords: AI and Machine Learning; Sales; Business Strategy; Market Entry and Exit
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Gupta, Sunil, and Frank V. Cespedes. "How One Company Used AI to Broaden Its Customer Base." Harvard Business Review (website) (March 27, 2025).
  • 2024
  • Working Paper

The Wade Test: Generative AI and CEO Communication

By: Prithwiraj Choudhury, Bart S. Vanneste and Amirhossein Zohrehvand
Can generative artificial intelligence (Gen-AI) transform the role of the CEO? This study investigates whether Gen-AI can mimic a human CEO and whether employees display aversion to Gen-AI communication. We present a framework of Gen-AI aversion that distinguishes... View Details
Keywords: Business or Company Management; AI and Machine Learning; Perception; Communication
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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. (Revised May 2025.)
  • April 1, 2024
  • Other Article

Paying For AI In Healthcare: Setting The Right Precedent Amidst Growing Use

By: Mitchell Tang, Kaylee Wilson and Ateev Mehrotra
Keywords: Health Care and Treatment; AI and Machine Learning; Cost
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Tang, Mitchell, Kaylee Wilson, and Ateev Mehrotra. "Paying For AI In Healthcare: Setting The Right Precedent Amidst Growing Use." Health Affairs Forefront (April 1, 2024).
  • November–December 2024
  • Article

Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing

By: Kirk Bansak and Elisabeth Paulson
This study proposes two new dynamic assignment algorithms to match refugees and asylum seekers to geographic localities within a host country. The first, currently implemented in a multi-year pilot in Switzerland, seeks to maximize the average predicted employment... View Details
Keywords: AI and Machine Learning; Refugees; Geographic Location; Employment
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Bansak, Kirk, and Elisabeth Paulson. "Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing." Operations Research 72, no. 6 (November–December 2024): 2375–2390.
  • July 2024 (Revised December 2024)
  • Case

Compass Ethics: Governing Through Ethical Principles at WeCorp Industries

By: Elisabeth Kempf and Jesse M. Shapiro
Andrew Hill is Chief Information Officer at WeCorp, a UK-based defense technology startup specializing in drone technology. WeCorp faces decisions about international licensing and AI integration in its drones. In partnership with Compass Ethics, Hill aims to establish... View Details
Keywords: Business Startups; Decision Making; Ethics; Entrepreneurial Finance; AI and Machine Learning; Technology Industry; United Kingdom
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Kempf, Elisabeth, and Jesse M. Shapiro. "Compass Ethics: Governing Through Ethical Principles at WeCorp Industries." Harvard Business School Case 224-105, July 2024. (Revised December 2024.)
  • 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
Keywords: Cybersecurity; Copyright; AI and Machine Learning; Analytics and Data Science
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Olagoke, Lukman, Salil Vadhan, and Seth Neel. "Black-box Training Data Identification in GANs via Detector Networks." Working Paper, October 2023.
  • 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
Keywords: Social Media; AI and Machine Learning; Brands and Branding; Power and Influence
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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.
  • October 2024 (Revised April 2025)
  • Case

Nvidia

By: Andy Wu and Matt Higgins
This case study examines Nvidia's strategic pivot from gaming GPUs to becoming a leader in general-purpose computing and AI. It explores how Nvidia leveraged its GPU architecture to dominate the growing fields of data center acceleration and AI training, outpacing... View Details
Keywords: Strategy; Technological Innovation; AI and Machine Learning; Product Development; Manufacturing Industry; Technology Industry; Electronics Industry; United States; China; Taiwan
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Wu, Andy, and Matt Higgins. "Nvidia." Harvard Business School Case 725-383, October 2024. (Revised April 2025.)
  • 2023
  • Working Paper

Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness

By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details
Keywords: AI and Machine Learning; Forecasting and Prediction; Prejudice and Bias
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Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
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