Publications
Publications
Show Results For
- All HBS Web
(5,598)
- Faculty Publications (1,086)
Page 1 of 1,086
Results →
- June 2025
- Article
Ideation with Generative AI—In Consumer Research and Beyond
By: Julian De Freitas, G. Nave and Stefano Puntoni
The use of large language models (LLMs) in consumer research is rapidly evolving, with applications including synthetic data generation, data analysis, and more. However, their role in creative ideation—a cornerstone of consumer research—remains underexplored. Drawing... View Details
- Working Paper
Shifting Work Patterns with Generative AI
By: Eleanor W. Dillon, Sonia Jaffe, Nicole Immorlica and Christopher T. Stanton
We present evidence on how generative AI changes the work patterns of knowledge workers using
data from a 6-month-long, cross-industry, randomized field experiment. Half of the 7,137 workers
in the study received access to a generative AI tool integrated into the... View Details
- May 2025
- Case
Windsurf and the AI Code Assistant Market
By: Suraj Srinivasan, Sudhanshu Nath Mishra and Radhika Kak
In April 2025, the founding team of Windsurf, an AI start-up specializing in code generation gathered in Mountain View, California, to assess its remarkable year of growth. The company had scaled from a niche GitHub Copilot alternative to a breakout player with over... View Details
- April 2025
- Background Note
Climate Change Adaptation with Artificial Intelligence and Machine Learning
By: Michael W. Toffel and Nabig Chaudhry
Artificial Intelligence (AI) and machine learning (ML) have emerged as powerful tools to address climate change. This note summarizes a wide range of the uses of AI/ML to drive climate change adaptation and resilience, the measures organizations and governments are... View Details
- April 2025 (Revised May 2025)
- Case
Adobe: GenAI Opportunity or Threat?
By: Sunil Gupta, Rajiv Lal and Allison Ciechanover
In December 2022, Adobe CEO Shantanu Narayen faced a pivotal strategic decision due to the rapid rise of generative AI image models from OpenAI, Midjourney, and StabilityAI. Adobe, a leader in digital media and marketing software with a 40-year legacy of innovation and... View Details
- April 2025
- Case
The CHIPS Program Office (Abridged)
By: Mitch Weiss and Sebastian Negron-Reichard
In February 2023, U.S. Commerce Secretary Gina Raimondo weighed signing off on a Notice of Funding Opportunity (“NOFO”) with at least one unconventional provision: a pre-application (“pre-app”) to the actual application for parts of $39 billion in direct semiconductor... View Details
- April 2025
- Article
The Impact of Minority Representation at Mortgage Lenders
By: W. Scott Frame, Ruidi Huang, Erica Jiang, Yeonjoon Lee, Will Liu, Erik J. Mayer and Adi Sunderam
We study links between the labor market for loan officers and access to mortgage credit. Using novel data matching the (near) universe of mortgage applications to loan officers, we find that minorities are significantly underrepresented among loan officers. Minority... View Details
- 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
- March 2025 (Revised May 2025)
- Case
Xfund and Sam Altman: Finding Harvard's Best Generative AI Founders
By: Suraj Srinivasan
On May 1, 2024, Xfund Managing Partners Patrick Chung and Brandon Farwell, hosted a high-stakes venture pitch session designed to select one startup for a minimum $100,000 investment. This “Xperiment Stake” competition, dedicated to startups in the Generative AI... View Details
- March 2025
- Case
Skylight: Hit Product or Scalable Company?
By: Rembrand Koning, Christina Wallace and Jeff Huizinga
Skylight's leadership faces a critical decision: should they abandon the struggling Calendar product to focus on their successful Frame business, or double down on potential growth... View Details
- March 2025
- Case
Metaphysic AI: Rethinking the Value of Human Expertise
By: Zoë B. Cullen, Shikhar Ghosh and Shweta Bagai
In early 2025, Thomas Graham, CEO of Metaphysic, a leading AI generative video company confronted fundamental questions about who should control digital identity in a world where AI could perfectly recreate human likeness. Founded in 2021, Metaphysic first rose to fame... View Details
- 2025
- Working Paper
Incentive-Compatible Recovery from Manipulated Signals, with Applications to Decentralized Physical Infrastructure
By: Jason Milionis, Jens Ernstberger, Joseph Bonneau, Scott Duke Kominers and Tim Roughgarden
We introduce the first formal model capturing the elicitation of unverifiable information from a party (the "source") with implicit signals derived by other players (the "observers"). Our model is motivated in part by applications in decentralized physical... View Details
- March 2025
- Article
Does Communicating Measurable Diversity Goals Attract or Repel Historically Marginalized Job Applicants? Evidence from the Lab and Field
By: Erika L. Kirgios, Ike Silver and Edward H. Chang
Many organizations struggle to attract a demographically diverse workforce. How does adding a measurable goal to a public diversity commitment—for example, “We care about diversity” versus “We care about diversity and plan to hire at least one woman or racial minority... View Details
- 2025
- Working Paper
Discrimination, Rejection, and Job Search
By: Anne Boring, Katherine Coffman, Dylan Glover and María José González-Fuentes
We investigate how candidates’ willingness to apply responds to (potential) discrimination and rejection using a simulated labor market. Past work has shown that “blinding” job applications reduces discrimination and increases the rate at which women are hired. Our... View Details
- February 2025
- Case
Fly, Fix, Fly at True Anomaly
By: Joshua Lev Krieger, Jim Matheson, Fiona Murray and David Allen
How should companies learn from failure? Founded by four U.S. Space Force warfighters, the tough tech startup True Anomaly wanted to compete with major defense contractors to supply the U.S. Department of Defense with satellites and software that could help protect... View Details
- February 2025
- Case
Blue Owl Financing of Ping Identity
By: Victoria Ivashina and Srimayi Mylavarapu
In the fall of 2022, Blue Owl Capital's investment committee evaluated a potential investment in the technology sector. The proposed transaction centered on Ping Identity Corporation (“Ping”), a fast-growing identity access management (IAM) software company that was... View Details
- 2025
- Working Paper
Blockchain Adoption and Audit Quality
By: Mei Luo, Daniel Rabetti and Shuangchen Yu
This study examines the impact of blockchain adoption in the corporate setting. Specifically, we provide comprehensive empirical support to recent theory (Cao, Cong, and Young, 2024) proposing that blockchain adoption positively affects endogenous audit quality and... View Details
- February 2025
- Article
Disclosure, Humanizing, and Contextual Vulnerability of Generative AI Chatbots
By: Julian De Freitas and I. Glenn Cohen
In the wake of recent advancements in generative AI, regulatory bodies are trying to keep pace. One key decision is whether to require app makers to disclose the use of generative AI-powered chatbots in their products. We suggest that some generative AI-based chatbots... View Details
- January 24, 2025
- Article
Behaviorally Designed Training Leads to More Diverse Hiring
By: Cansin Arslan, Edward H. Chang, Siri Chilazi, Iris Bohnet and Oliver P. Hauser
Many organizations have shown interest in increasing the diversity of their workforces for various reasons. Collectively, they have spent millions of dollars and countless employee hours on diversity training. Yet, there is little empirical evidence that such training... View Details
- January 2025
- Technical Note
AI vs Human: Analyzing Acceptable Error Rates Using the Confusion Matrix
By: Tsedal Neeley and Tim Englehart
This technical note introduces the confusion matrix as a foundational tool in artificial intelligence (AI) and large language models (LLMs) for assessing the performance of classification models, focusing on their reliability for decision-making. A confusion matrix... View Details