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- 2024
- Working Paper
AI Companions Reduce Loneliness
By: Julian De Freitas, Ahmet K Uguralp, Zeliha O Uguralp and Puntoni Stefano
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...
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De Freitas, Julian, Ahmet K Uguralp, Zeliha O Uguralp, and Puntoni Stefano. "AI Companions Reduce Loneliness." Harvard Business School Working Paper, No. 24-078, June 2024.
- 2024
- Working Paper
Private Equity and Digital Transformation
By: Brian K. Baik, Wilbur Chen and Suraj Srinivasan
We study the role which private equity (PE) plays in digital transformation. We find that PE investment is associated with greater investments into portfolio firm’s digital technologies, as measured by IT expenditures and the hiring demand for AI skills. This...
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Keywords:
Digital Transformation;
Private Equity;
Selection and Staffing;
Investment Portfolio;
Value Creation
Baik, Brian K., Wilbur Chen, and Suraj Srinivasan. "Private Equity and Digital Transformation." Harvard Business School Working Paper, No. 24-070, May 2024.
- 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,...
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Keywords:
AI and Machine Learning;
Valuation;
Technological Innovation;
Open Source Distribution;
Patents;
Policy;
Knowledge Sharing;
Technology Industry
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...
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Keywords:
Artificial Intelligence;
AI;
Customer Relationship Management;
CRM;
Chatbots;
Sales Management;
Generative Ai;
Software;
SaaS;
Marketing;
Sales;
AI and Machine Learning;
Technology Industry;
United States
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...
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Keywords:
AI
- 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...
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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–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.
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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.
- April 2024 (Revised May 2024)
- Case
Anthropic: Building Safe AI
By: Shikhar Ghosh and Shweta Bagai
In March 2024, Anthropic, a leading AI safety and research company, made headlines with the launch of Claude 3, its most advanced AI model. This marked Anthropic’s bold entry into the multimodal GenAI domain, showcasing capabilities extending to both image and text...
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Ghosh, Shikhar, and Shweta Bagai. "Anthropic: Building Safe AI." Harvard Business School Case 824-129, April 2024. (Revised May 2024.)
- 2024
- Working Paper
Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions
By: Caleb Kwon, Ananth Raman and Jorge Tamayo
We investigate whether corporate officers should grant managers discretion to override AI-driven demand forecasts and labor scheduling tools. Analyzing five years of administrative data from a large grocery retailer using such an AI tool, encompassing over 500 stores,...
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Keywords:
AI and Machine Learning;
Forecasting and Prediction;
Working Conditions;
Performance Productivity
Kwon, Caleb, Ananth Raman, and Jorge Tamayo. "Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions." Working Paper, April 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),...
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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 April 2024)
- Case
Coursera's Foray into GenAI
By: Suraj Srinivasan, Michael Parzen and Radhika Kak
In early 2023, Maggioncalda, CEO of US EdTech firm Coursera, launched Project Genesis to develop a strategy for incorporating GenAI capabilities into the firm's offerings, asking his teams to focus on value to the firm and cost of implementation. The team identified...
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Keywords:
Business Model;
AI and Machine Learning;
Brands and Branding;
Business Strategy;
Competitive Advantage;
Technological Innovation;
Education Industry;
Technology Industry;
United States
Srinivasan, Suraj, Michael Parzen, and Radhika Kak. "Coursera's Foray into GenAI." Harvard Business School Case 124-089, March 2024. (Revised April 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...
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- 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....
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- 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...
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Weiss, Mitchell. "'Storrowed': A Generative AI Exercise." Harvard Business School Exercise 824-188, March 2024.
- March 2024
- 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...
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- 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...
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Keywords:
Sales Management;
Digital Tools;
Sales;
Marketing Channels;
Technology Adoption;
Brands and Branding
Cespedes, Frank V., and Georg Krentzel. "Integrating Digital Tools into Every Stage of Your Sales Strategy." Harvard Business Review (website) (March 7, 2024).
- March 2024 (Revised June 2024)
- 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...
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Keywords:
Artificial Intelligence;
Board Of Directors;
Board Decisions;
Board Dynamics;
Business Ethics;
Corporate Boards;
Governance Changes;
Governance Structure;
Leadership Change;
Legal Aspects Of Business;
Nonprofit;
Nonprofit Governance;
Open Source;
Partnerships;
Regulation;
Strategy And Execution;
Technological Change;
AI and Machine Learning;
Corporate Governance;
Leadership;
Management;
Mission and Purpose;
Technological Innovation;
Technology Industry;
San Francisco;
United States
Paine, Lynn S., Suraj Srinivasan, and Will Hurwitz. "Governing OpenAI (A)." Harvard Business School Case 324-103, March 2024. (Revised June 2024.)
- February 26, 2024
- Article
Making Workplaces Safer Through Machine Learning
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
Machine learning algorithms can dramatically improve regulatory effectiveness. This short article describes the authors' scholarly work that shows how the U.S. Occupational Safety and Health Administration (OSHA) could have reduced nearly twice as many occupational...
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Keywords:
Government Experimentation;
Auditing;
Inspection;
Evaluation;
Process Improvement;
Government Administration;
AI and Machine Learning;
Safety;
Governing Rules, Regulations, and Reforms
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Making Workplaces Safer Through Machine Learning." Regulatory Review (February 26, 2024).
- February 2024
- Case
Taffi: Entrepreneurship in Saudi Arabia
By: Paul A. Gompers and Fares Khrais
Taffi was a tech-enabled fashion styling startup founded by Shahad Geoffrey in Saudi Arabia in 2020. Within three years of operating, Geoferry had pivoted the business multiple times. In 2023, Geoferry was attempting the business’s most ambitious pivot yet, shifting...
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- February 2024
- Teaching Note
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
Teaching Note for HBS Case No. 224-029. Levi Strauss & Co. (“Levi Strauss”) partnered with the IT services company Wipro to incorporate more sophisticated methods, such as machine learning, into their financial forecasting process starting in 2018. The decision to...
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