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      • January 2025
      • Case

      AI Meets VC: The Data-Driven Revolution at Quantum Light Capital

      By: Lauren Cohen, Grace Headinger and Sophia Pan
      Ilya Kondrashov, CEO of Quantum Light Capital, was driven to harness AI for identifying high-potential scale-ups. Collaborating with Nik Storonsky, founder of Revolut, the duo observed that most venture capital (VC) decisions were heavily influenced by emotion, with... View Details
      Keywords: Artificial Intelligence; Business Finance; Data Analysis; Angel Investors; Cognitive Biases; Scale; Venture Capital; Investment; Business Model; Forecasting and Prediction; Technological Innovation; Innovation Strategy; Behavior; Cognition and Thinking; Public Opinion; Private Sector; Business Strategy; Competitive Advantage; Business Earnings; Behavioral Finance; AI and Machine Learning; Analytics and Data Science; Business Startups; Financial Services Industry; London; United Kingdom
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      Cohen, Lauren, Grace Headinger, and Sophia Pan. "AI Meets VC: The Data-Driven Revolution at Quantum Light Capital." Harvard Business School Case 225-053, January 2025.
      • January 2025
      • Case

      Ontra: Embracing GenAI in the Legal Technology Industry

      By: Christopher Stanton and George Gonzalez
      Ontra built a network of legal professionals to enable financial institutions to outsource contract negotiations. The rise of generative AI inspired the company to build software solutions to streamline its processes through automation. Now company leadership must... View Details
      Keywords: Transformation; AI and Machine Learning; Applications and Software; Organizational Change and Adaptation; Organizational Culture; Business Strategy; Technology Industry; Legal Services Industry; United States
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      Stanton, Christopher, and George Gonzalez. "Ontra: Embracing GenAI in the Legal Technology Industry." Harvard Business School Case 825-076, January 2025.
      • January 2025
      • Case

      The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation (A)

      By: Tsedal Neeley, Levi Stroud, Ruth Page and Dave Habeeb
      Pre-abstract: This multimedia case should be assigned to students in advance of class. Instructors should consider the timing of making the (B) Case videos available to students, as they may reveal key case details.

      Abstract: Florian Hillen, co-founder... View Details
      Keywords: Diagnostics; Organization Design; Change Management; Disruption; Transformation; Health Care and Treatment; AI and Machine Learning; Technology Adoption; Technological Innovation; Management Style; Organizational Culture; Success; Technology Industry; Health Industry; United States
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      Neeley, Tsedal, Levi Stroud, Ruth Page, and Dave Habeeb. "The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation (A)." Harvard Business School Multimedia/Video Case 425-720, January 2025.
      • January 2025
      • Supplement

      The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation (B)

      By: Tsedal Neeley, Levi Stroud, Ruth Page and Dave Habeeb
      Pre-abstract: This multimedia case should be assigned to students in advance of class. Instructors should consider the timing of making the (B) Case videos available to students, as they may reveal key case details.

      Abstract: Florian Hillen, co-founder... View Details
      Keywords: Diagnostics; Organization Design; Change Management; Disruption; Transformation; Health Care and Treatment; AI and Machine Learning; Technology Adoption; Technological Innovation; Management Style; Organizational Culture; Success; Technology Industry; Health Industry; United States
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      Neeley, Tsedal, Levi Stroud, Ruth Page, and Dave Habeeb. "The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation (B)." Harvard Business School Multimedia/Video Supplement 425-721, January 2025.
      • 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
      Keywords: AI and Machine Learning; Demographics; Prejudice and Bias
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      Samure, Roger, Julian De Freitas, and Stefano Puntoni. "Humor as a Window into Generative AI Bias." Art. 1326. Scientific Reports 15 (2025).
      • January 2025
      • Article

      Reducing Prejudice with Counter-stereotypical AI

      By: Erik Hermann, Julian De Freitas and Stefano Puntoni
      Based on a review of relevant literature, we propose that the proliferation of AI with human-like and social features presents an unprecedented opportunity to address the underlying cognitive and affective drivers of prejudice. An approach informed by the psychology of... View Details
      Keywords: Prejudice and Bias; AI and Machine Learning; Interpersonal Communication; Social and Collaborative Networks
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      Hermann, Erik, Julian De Freitas, and Stefano Puntoni. "Reducing Prejudice with Counter-stereotypical AI." Consumer Psychology Review 8, no. 1 (January 2025): 75–86.
      • 2025
      • Article

      Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments

      By: Kosuke Imai and Michael Lingzhi Li
      Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
      Keywords: AI and Machine Learning; Mathematical Methods; Analytics and Data Science
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      Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics 43, no. 1 (2025): 256–268.
      • January–February 2025
      • Article

      Want Your Company to Get Better at Experimentation?: Learn Fast by Democratizing Testing

      By: Iavor Bojinov, David Holtz, Ramesh Johari, Sven Schmit and Martin Tingley
      For years, online experimentation has fueled the innovations of leading tech companies, enabling them to rapidly test and refine new ideas, optimize product features, personalize user experiences, and maintain a competitive edge. The widespread availability and lower... View Details
      Keywords: Technological Innovation; AI and Machine Learning; Analytics and Data Science; Product Development; Competitive Advantage
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      Bojinov, Iavor, David Holtz, Ramesh Johari, Sven Schmit, and Martin Tingley. "Want Your Company to Get Better at Experimentation? Learn Fast by Democratizing Testing." Harvard Business Review 103, no. 1 (January–February 2025): 96–103.
      • January–February 2025
      • Article

      Why People Resist Embracing AI

      By: Julian De Freitas
      The success of AI depends not only on its capabilities, which are becoming more advanced each day, but on people’s willingness to harness them. Unfortunately, many people view AI negatively, fearing it will cause job losses, increase the likelihood that their personal... View Details
      Keywords: AI and Machine Learning; Technology Adoption; Perception
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      De Freitas, Julian. "Why People Resist Embracing AI." Harvard Business Review 103, no. 1 (January–February 2025): 52–56.
      • December 18, 2024
      • Article

      Is AI the Right Tool to Solve That Problem?

      By: Paolo Cervini, Chiara Farronato, Pushmeet Kohli and Marshall W Van Alstyne
      While AI has the potential to solve major problems, organizations embarking on such journeys of often encounter obstacles. They include a dearth of high-quality data; too many possible solutions; the lack of a clear, measurable objective; and difficulty in identifying... View Details
      Keywords: Artificial Intelligence; AI and Machine Learning; Problems and Challenges
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      Cervini, Paolo, Chiara Farronato, Pushmeet Kohli, and Marshall W Van Alstyne. "Is AI the Right Tool to Solve That Problem?" Harvard Business Review (website) (December 18, 2024).
      • December 2024 (Revised January 2025)
      • Technical Note

      A Guide to the Vocabulary, Evolution, and Impact of Artificial Intelligence (AI)

      By: Shane Greenstein, Nathaniel Lovin, Scott Wallsten, Kerry Herman and Susan Pinckney
      A note on the vocabulary, evolution, and impact of AI. View Details
      Keywords: Artificial Intelligence; Software; AI and Machine Learning; Technology Adoption; Technological Innovation; Technology Industry
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      Greenstein, Shane, Nathaniel Lovin, Scott Wallsten, Kerry Herman, and Susan Pinckney. "A Guide to the Vocabulary, Evolution, and Impact of Artificial Intelligence (AI)." Harvard Business School Technical Note 625-039, December 2024. (Revised January 2025.)
      • December 2024
      • Case

      Blue Cross Blue Shield of Michigan (BCBSM): The AI Journey

      By: Shikhar Ghosh
      In early 2024, Bill Fandrich, Executive VP and CIO of Blue Cross Blue Shield of Michigan (BCBSM), faced a critical decision about AI adoption within the organization. Fandrich had championed AI implementation at BCBSM. After successfully developing three AI... View Details
      Keywords: Blue Cross; Automation; Generative Ai; Health Insurance; Insurance Companies; Innovation; IT Strategy; Organizational Transformations; Technology; Non-profit; AI and Machine Learning; Health; Digital Strategy; Digital Transformation; Leadership; Technology Adoption; Job Cuts and Outsourcing; Innovation Strategy; Health Industry; Insurance Industry; Michigan
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      Ghosh, Shikhar. "Blue Cross Blue Shield of Michigan (BCBSM): The AI Journey." Harvard Business School Case 825-082, December 2024.
      • 2024
      • Working Paper

      Displacement or Complementarity? The Labor Market Impact of Generative AI

      By: Wilbur Xinyuan Chen, Suraj Srinivasan and Saleh Zakerinia
      Generative AI is poised to reshape the labor market, affecting cognitive and white-collar occupations in ways distinct from past technological revolutions. This study examines whether generative AI displaces workers or augments their jobs by analyzing labor demand and... View Details
      Keywords: Generative Ai; Labor Market; Automation And Augmentation; Labor; AI and Machine Learning; Competency and Skills
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      Chen, Wilbur Xinyuan, Suraj Srinivasan, and Saleh Zakerinia. "Displacement or Complementarity? The Labor Market Impact of Generative AI." Harvard Business School Working Paper, No. 25-039, December 2024.
      • 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.)
      • November 2024
      • Case

      AlphaGo (A): Birth of a New Intelligence

      By: Shikhar Ghosh and Shweta Bagai
      This case, the first of a three-part series, traces DeepMind's evolution from its 2010 founding through its acquisition by Google in 2014. Often referred to as the "Apollo project" of artificial intelligence, DeepMind used games as a testing ground to develop AI... View Details
      Keywords: AI and Machine Learning; Technology Adoption; Games, Gaming, and Gambling; Technological Innovation; Creativity; Technology Industry; South Korea; China; United States
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      Ghosh, Shikhar, and Shweta Bagai. "AlphaGo (A): Birth of a New Intelligence." Harvard Business School Case 825-073, November 2024.
      • November 2024
      • Supplement

      AlphaGo (B): Birth of a New Intelligence

      By: Shikhar Ghosh and Shweta Bagai
      This case, the second in a three-part series, explores DeepMind's evolution from developing game-specific AI to more generalized learning systems. Following AlphaGo's 2017 victory over the Go world champion, DeepMind introduced two revolutionary systems that eliminated... View Details
      Keywords: AI and Machine Learning; Games, Gaming, and Gambling; Technological Innovation; Disruptive Innovation; Innovation Leadership; Information Technology Industry; United States; Russia; China
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      Ghosh, Shikhar, and Shweta Bagai. "AlphaGo (B): Birth of a New Intelligence." Harvard Business School Supplement 825-074, November 2024.
      • November 2024
      • Supplement

      AlphaGo (C): Birth of a New Intelligence

      By: Shikhar Ghosh and Shweta Bagai
      This case, the final of a three-part series, explores DeepMind's pivotal transition from mastering games to solving real-world scientific challenges. In December 2020, DeepMind's AI system AlphaFold 2 achieved a breakthrough by solving protein folding—a 50-year-old... View Details
      Keywords: Autonomy; Deep Learning; Drug Discovery; Healthcare Innovation; Neural Networks; Scientific Research; Technology Startup; AI and Machine Learning; Technological Innovation; Research and Development; Business Model; Business Strategy; Open Source Distribution; Technology Industry; United States
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      Ghosh, Shikhar, and Shweta Bagai. "AlphaGo (C): Birth of a New Intelligence." Harvard Business School Supplement 825-075, November 2024.
      • 2024
      • Working Paper

      Scaling Core Earnings Measurement with Large Language Models

      By: Matthew Shaffer and Charles CY Wang
      We study the application of large language models (LLMs) to the estimation of core earnings, i.e., a firm's persistent profitability from its core business activities. This construct is central to investors' assessments of economic performance and valuations. However,... View Details
      Keywords: Large Language Models; AI and Machine Learning; Accounting; Profit; Corporate Disclosure; Analytics and Data Science; Measurement and Metrics
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      Shaffer, Matthew, and Charles CY Wang. "Scaling Core Earnings Measurement with Large Language Models." Working Paper, November 2024.
      • 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.)
      • November 2024 (Revised January 2025)
      • Case

      MiDAS: Automating Unemployment Benefits

      By: Shikhar Ghosh and Shweta Bagai
      In 2015, the state of Michigan considered whether to nominate its Michigan Integrated Data Automated System (MiDAS) for a prestigious state technology award. Launched in 2013 amid severe budget pressures, the $47 million automated fraud detection system was designed to... View Details
      Keywords: Artificial Intelligence; AI; Machine Learning Models; Algorithmic Data; Automation; Benefits; Compensation; Cost Reduction; Government; Fraud; Government Technology; Public Sector; Systems; Systems Integration; Unemployment Insurance; Waste Heat Recovery; AI and Machine Learning; Government Administration; Insurance; Decision Making; Digital Transformation; Employment; Public Administration Industry; United States; Michigan
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      Ghosh, Shikhar, and Shweta Bagai. "MiDAS: Automating Unemployment Benefits." Harvard Business School Case 825-100, November 2024. (Revised January 2025.)
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