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      • May 2024 (Revised February 2025)
      • Case

      Lowe's: Improving the Total Home Strategy

      By: Elie Ofek, K. Shelette Stewart and Alicia Dadlani
      In 2023, Marvin Ellison, CEO of Lowe’s, contemplated enhancements to the company’s Total Home Strategy to accelerate performance and grow market share. In the last five years since becoming CEO, Ellison had championed a turnaround of the company, completing a... View Details
      Keywords: Growth and Development Strategy; E-commerce; Competition; Brands and Branding; Business Strategy; Retail Industry; United States; North Carolina
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      Ofek, Elie, K. Shelette Stewart, and Alicia Dadlani. "Lowe's: Improving the Total Home Strategy." Harvard Business School Case 524-054, May 2024. (Revised February 2025.)
      • 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.
      • May 2024
      • Supplement

      HubSpot and Motion AI (B): Generative AI Opportunities

      By: Jill Avery
      The technologies driving artificial intelligence (AI) had progressed significantly since HubSpot’s acquisition of Motion AI in 2017. Generative AI was the newest major development. Software-as-a-service (SaaS) companies such as HubSpot were analyzing how generative AI... View Details
      Keywords: Artificial Intelligence; CRM; Chatbots; Sales Management; Generative Ai; SaaS; Marketing; Sales; AI and Machine Learning; Customer Relationship Management; Applications and Software; Technological Innovation; Competitive Advantage; Technology Industry; United States
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      Avery, Jill. "HubSpot and Motion AI (B): Generative AI Opportunities." Harvard Business School Supplement 524-088, May 2024.
      • May 2024
      • Teaching Note

      AI Wars

      By: Andy Wu and Matt Higgins
      Teaching Note for HBS Case No. 723-434. In 2024, the world was looking to Google to see what the search giant and long-time putative technical leader in artificial intelligence (AI) would do to compete in the massively hyped technology of generative AI popularized over... View Details
      Keywords: AI; Trends; AI and Machine Learning; Public Opinion; Technological Innovation; Competitive Advantage; Technology Industry
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      Wu, Andy, and Matt Higgins. "AI Wars." Harvard Business School Teaching Note 724-482, May 2024.
      • May 2024
      • Teaching Note

      AI21 Labs in 2023: Strategy for Generative AI

      By: David Yoffie
      Teaching Note for HBS Case 724-383. The case has 3 important teaching purposes: First, what are the advantages and disadvantages of imitation? (e.g., Should AI21 imitate OpenAI with a chatbot?) Second, what are the advantages and disadvantages of keeping new technology... View Details
      Keywords: AI; Generative Ai; Generative Models; AI and Machine Learning; Innovation Strategy; Growth and Development Strategy; Business Model; Business Startups; Open Source Distribution; Competitive Advantage; Technology Industry; Israel
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      Yoffie, David. "AI21 Labs in 2023: Strategy for Generative AI." Harvard Business School Teaching Note 724-461, May 2024.
      • 2024
      • Working Paper

      Old Moats for New Models: Openness, Control, and Competition in Generative AI

      By: Pierre Azoulay, Joshua L. Krieger and Abhishek Nagaraj
      Drawing insights from the field of innovation economics, we discuss the likely competitive environment shaping generative AI advances. Central to our analysis are the concepts of appropriability—whether firms in the industry are able to control the knowledge generated... View Details
      Keywords: Technological Innovation; AI and Machine Learning; Open Source Distribution; Policy
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      Azoulay, Pierre, Joshua L. Krieger, and Abhishek Nagaraj. "Old Moats for New Models: Openness, Control, and Competition in Generative AI." NBER Working Paper Series, No. 7442, 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.
      • 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.)
      • April 2024
      • Article

      A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification

      By: Hsin-Hsiao Scott Wang, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow and Caleb Nelson
      Backgrounds: Urinary Tract Dilation (UTD) classification has been designed to be a more objective grading system to evaluate antenatal and post-natal UTD. Due to unclear association between UTD classifications to specific anomalies such as vesico-ureteral reflux (VUR),... View Details
      Keywords: Health Disorders; Health Testing and Trials; AI and Machine Learning; Health Industry
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      Wang, Hsin-Hsiao Scott, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow, and Caleb Nelson. "A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification." Journal of Pediatric Urology 20, no. 2 (April 2024): 271–278.
      • March 2024 (Revised November 2024)
      • Case

      Kawasaki Heavy Industries Bets on Clean Hydrogen

      By: Gunnar Trumbull, Nobuo Sato and Akiko Kanno
      Kawasaki Heavy Industries (KHI), an engineering manufacturer headquartered in Japan, was aiming to scale up its hydrogen production and establish a global hydrogen supply chain. The initiative was in line with Japan's energy strategy, as the country seeks to transition... View Details
      Keywords: Renewable Energy; Demand and Consumers; Competition; Growth and Development Strategy; Infrastructure; Supply Chain; Manufacturing Industry; Energy Industry
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      Trumbull, Gunnar, Nobuo Sato, and Akiko Kanno. "Kawasaki Heavy Industries Bets on Clean Hydrogen." Harvard Business School Case 724-035, March 2024. (Revised November 2024.)
      • 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.)
      • March 2024
      • Simulation

      'Storrowed'

      By: Mitchell Weiss
      The game was built to accompany "Storrowed": A Generative AI Exercise, available through Harvard Business Publishing. The game adds a timing element to "Storrowed" and enables the teacher to reward teams for strong prompts or penalize teams for believing AI... View Details
      Keywords: AI and Machine Learning; Decision Choices and Conditions; Risk and Uncertainty
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      Weiss, Mitchell. "'Storrowed'." Harvard Business School Simulation 824-714, March 2024.
      • 2024
      • Working Paper

      The Cram Method for Efficient Simultaneous Learning and Evaluation

      By: Zeyang Jia, Kosuke Imai and Michael Lingzhi Li
      We introduce the "cram" method, a general and efficient approach to simultaneous learning and evaluation using a generic machine learning (ML) algorithm. In a single pass of batched data, the proposed method repeatedly trains an ML algorithm and tests its empirical... View Details
      Keywords: AI and Machine Learning
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      Jia, Zeyang, Kosuke Imai, and Michael Lingzhi Li. "The Cram Method for Efficient Simultaneous Learning and Evaluation." Working Paper, March 2024.
      • March 2024
      • Teaching Note

      'Storrowed': A Generative AI Exercise

      By: Mitchell Weiss
      Teaching Note for HBS Exercise No. 824-188. “Storrowed” is an exercise to help participants raise their proficiency with generative AI. It begins by highlighting a problem: trucks getting wedged underneath bridges in Boston, Massachusetts on the city’s Storrow Drive.... View Details
      Keywords: AI and Machine Learning; Entrepreneurship; Innovation and Invention; Government Administration; Transportation Industry; Public Administration Industry
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      Weiss, Mitchell. "'Storrowed': A Generative AI Exercise." Harvard Business School Teaching Note 824-189, March 2024.
      • March 2024
      • Exercise

      'Storrowed': A Generative AI Exercise

      By: Mitchell Weiss
      "Storrowed" is an exercise to help participants raise their capacity and curiosity for generative AI. It focuses on generative AI for problem understanding and ideation, but can be adapted for use more broadly. Participants use generative AI tools to understand a... View Details
      Keywords: AI and Machine Learning; Problems and Challenges
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      Weiss, Mitchell. "'Storrowed': A Generative AI Exercise." Harvard Business School Exercise 824-188, March 2024.
      • March 2024 (Revised June 2025)
      • Teaching Note

      CoPilot(s): Generative AI at Microsoft and GitHub

      By: Frank Nagle and Maria P. Roche
      This teaching note is the companion to case N9-624-010 CoPilot(s): Generative AI at Microsoft and GitHub, which takes place in late 2021. The case briefly describes the history of both GitHub and Microsoft with a particular focus on open source software (OSS)—software... View Details
      Keywords: Mergers and Acquisitions; AI and Machine Learning; Applications and Software; Technological Innovation; Product Launch; Open Source Distribution; Product Development; Commercialization; Competition; Resource Allocation; Technology Industry
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      Nagle, Frank, and Maria P. Roche. "CoPilot(s): Generative AI at Microsoft and GitHub." Harvard Business School Teaching Note 724-452, March 2024. (Revised June 2025.)
      • March 7, 2024
      • Article

      Integrating Digital Tools into Every Stage of Your Sales Strategy

      By: Frank V. Cespedes and Georg Krentzel
      In their growth and customer-acquisition activities, most companies now face twin challenges: understanding and responding to omni-channel buying behavior and doing that without inadvertently decreasing sales productivity. Thirty years ago, Peter Drucker noted that... View Details
      Keywords: Sales Management; Digital Tools; Sales; Marketing Channels; Technology Adoption; Brands and Branding
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      Cespedes, Frank V., and Georg Krentzel. "Integrating Digital Tools into Every Stage of Your Sales Strategy." Harvard Business Review (website) (March 7, 2024).
      • 2023
      • Working Paper

      An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits

      By: Biyonka Liang and Iavor I. Bojinov
      Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details
      Keywords: Analytics and Data Science; AI and Machine Learning; Mathematical Methods
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      Liang, Biyonka, and Iavor I. Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
      • March 2024 (Revised May 2025)
      • Case

      Governing OpenAI (A)

      By: Lynn S. Paine, Suraj Srinivasan and Will Hurwitz
      In late November 2023, OpenAI’s new board of directors took stock of the situation. The company, which sought to develop artificial general intelligence (AGI)—computer systems with capabilities exceeding human abilities—was looking to regain its footing after a chaotic... View Details
      Keywords: Artificial Intelligence; Board Of Directors; Board Decisions; Board Dynamics; Corporate Boards; Governance Changes; Governance Structure; Leadership Change; Legal Aspects Of Business; Nonprofit Governance; Strategy And Execution; Technological Change; AI and Machine Learning; Corporate Governance; Leadership; Management; Mission and Purpose; Technological Innovation; Governing Rules, Regulations, and Reforms; Governing and Advisory Boards; Resignation and Termination; Ethics; Nonprofit Organizations; Open Source Distribution; Partners and Partnerships; Technology Industry; San Francisco; United States
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      Paine, Lynn S., Suraj Srinivasan, and Will Hurwitz. "Governing OpenAI (A)." Harvard Business School Case 324-103, March 2024. (Revised May 2025.)
      • March 2024 (Revised August 2024)
      • Case

      Darktrace: Scaling Cybersecurity and AI (A)

      By: Jeffrey F. Rayport and Alexis Lefort
      In 2023, Darktrace CEO Poppy Gustafsson was contemplating her growth strategy at a leading U.K.-based cybersecurity venture, launched in 2013 by a group of anti-terror cyber specialists, University of Cambridge mathematicians, and artificial intelligence (AI) experts.... View Details
      Keywords: Technology; Talent; Scaling; Entrepreneurship; Cybersecurity; Leadership; Business Growth and Maturation; Recruitment; Resignation and Termination; AI and Machine Learning; Growth and Development Strategy; Organizational Culture; Going Public; Technology Industry; United Kingdom; Europe; United States
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      Rayport, Jeffrey F., and Alexis Lefort. "Darktrace: Scaling Cybersecurity and AI (A)." Harvard Business School Case 824-092, March 2024. (Revised August 2024.)
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