Filter Results:
(1,633)
Show Results For
- All HBS Web
(12,701)
- Faculty Publications (1,633)
Show Results For
- All HBS Web
(12,701)
- Faculty Publications (1,633)
Learning
→
- March 2025
- Case
Niramai: An AI Solution to Save Lives
By: Rembrand Koning, Maria P. Roche and Kairavi Dey
Founded in 2017, Niramai developed Thermalytix, a breast cancer screening tool. Thermalytix used a high-resolution thermal sensing device and machine learning algorithms to analyze thermal images and detect tumors. Its patented solution leveraged big data analytics,... View Details
- 2025
- Working Paper
The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise
By: Fabrizio Dell'Acqua, Charles Ayoubi, Hila Lifshitz, Raffaella Sadun, Ethan Mollick, Lilach Mollick, Yi Han, Jeff Goldman, Hari Nair, Stew Taub and Karim R. Lakhani
We examine how artificial intelligence transforms the core pillars of collaboration—
performance, expertise sharing, and social engagement—through a pre-registered field
experiment with 776 professionals at Procter & Gamble, a global consumer packaged goods
company.... View Details
Keywords: Artificial Intelligence; Teamwork; Human-machine Interaction; Productivity; Skills; Innovation; Field Experiment; AI and Machine Learning; Groups and Teams; Competency and Skills; Performance Productivity; Collaborative Innovation and Invention; Product Development
Dell'Acqua, Fabrizio, Charles Ayoubi, Hila Lifshitz, Raffaella Sadun, Ethan Mollick, Lilach Mollick, Yi Han, Jeff Goldman, Hari Nair, Stew Taub, and Karim R. Lakhani. "The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise." Harvard Business School Working Paper, No. 25-043, March 2025.
- March 2025 (Revised April 2025)
- Case
Perplexity: Redefining Search
By: Suraj Srinivasan, Michelle Hu, Sriraghav Srinivasan and Radhika Kak
By early 2025, Perplexity had rapidly evolved from a modest startup into a popular "answer engine" valued at $9 billion. The company had boldly positioned itself as the disruptor to Google aiming to redefine search for the AI age. Through novel AI... View Details
Keywords: AI and Machine Learning; Venture Capital; Innovation Leadership; Technological Innovation; Internet and the Web; Business Startups; Competitive Strategy; Technology Industry; United States
Srinivasan, Suraj, Michelle Hu, Sriraghav Srinivasan, and Radhika Kak. "Perplexity: Redefining Search." Harvard Business School Case 125-093, March 2025. (Revised April 2025.)
- 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
Keywords: AI and Machine Learning; Venture Capital; Innovation Leadership; Technological Innovation; Business Startups; Competition; Technology Industry; United States
Srinivasan, Suraj. "Xfund and Sam Altman: Finding Harvard's Best Generative AI Founders." Harvard Business School Case 125-090, March 2025. (Revised May 2025.)
- 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
Keywords: Business Model; Ethics; AI and Machine Learning; Intellectual Property; Rights; Negotiation; Value; Motion Pictures and Video Industry; Technology Industry
Cullen, Zoë B., Shikhar Ghosh, and Shweta Bagai. "Metaphysic AI: Rethinking the Value of Human Expertise." Harvard Business School Case 825-146, March 2025.
- March 10, 2025
- Article
How Gen AI Could Change the Value of Expertise
By: Joseph Fuller, Matt Sigelman and Michael Fenlon
In the near future, gen AI is likely to affect some 50 million jobs, automating away elements of some jobs and augmenting workers’ abilities in others. The extent of those changes will compel companies to reshape their organizational structures and rethink their talent... View Details
Keywords: AI and Machine Learning; Job Cuts and Outsourcing; Organizational Structure; Talent and Talent Management; Personal Development and Career
Fuller, Joseph, Matt Sigelman, and Michael Fenlon. "How Gen AI Could Change the Value of Expertise." Harvard Business Review (website) (March 10, 2025).
- 2025
- Working Paper
How to Choose Among Technologies with Learning Curves: Making Better Investment Decisions
By: Christian Kaps and Arielle Anderer
Learning curves, the fact that technologies improve as a function of cumulative experience or investment, are desirable-think inexpensive solar panels or higher performing semiconductors. But, for firms that need to pick one technology among several candidates, such as... View Details
Keywords: Learning Curve; Technology; Innovation; Batteries; Energy Storage; Sequential Decision Making; TELCO; Exploration; Exploitation; Problems and Challenges; Cost vs Benefits; Technology Adoption; Battery Industry
Kaps, Christian, and Arielle Anderer. "How to Choose Among Technologies with Learning Curves: Making Better Investment Decisions." Working Paper, March 2025.
- March 2025
- Case
Harvey: AI for Lawyers
By: Suraj Srinivasan, Charles Krumholz and Radhika Kak
In early 2025, Winston Weinberg and Gabe Pereyra, co-founders of Harvey AI, reflected on the company’s meteoric rise as a pioneer in AI-powered legal technology. Since its founding in 2022, Harvey had transformed how lawyers approached research, drafting, and document... View Details
Keywords: Innovation Strategy; Business Startups; AI and Machine Learning; Technological Innovation; Growth and Development Strategy; Product Positioning; Legal Services Industry; Technology Industry; New York (city, NY); San Francisco; London
Srinivasan, Suraj, Charles Krumholz, and Radhika Kak. "Harvey: AI for Lawyers." Harvard Business School Case 125-087, March 2025.
- 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
Milionis, Jason, Jens Ernstberger, Joseph Bonneau, Scott Duke Kominers, and Tim Roughgarden. "Incentive-Compatible Recovery from Manipulated Signals, with Applications to Decentralized Physical Infrastructure." Working Paper, March 2025.
- March 2025
- Supplement
Intuition Robotics: An AI Companion for Older Adults (B)
By: Amit Goldenberg, Elie Ofek and Orna Dan
Two years after Intuition Robotics opted to pursue a business-to-government contract with the New York State Office of the Aging, and put direct-to-consumer efforts on the back burner, it was at a crossroads. The partnership had been successful, and the company had... View Details
- March 2025
- Article
Novice Risk Work: How Juniors Coaching Seniors on Emerging Technologies Such as Generative AI Can Lead to Learning Failures
By: Katherine C. Kellogg, Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Fabrizio Dell'Acqua, Edward McFowland III, François Candelon and Karim R. Lakhani
The literature on communities of practice demonstrates that a proven way for senior professionals to upskill
themselves in the use of new technologies that undermine existing expertise is to learn from junior
professionals. It notes that juniors may be better able... View Details
Keywords: Rank and Position; Competency and Skills; Technology Adoption; Experience and Expertise; AI and Machine Learning
Kellogg, Katherine C., Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Fabrizio Dell'Acqua, Edward McFowland III, François Candelon, and Karim R. Lakhani. "Novice Risk Work: How Juniors Coaching Seniors on Emerging Technologies Such as Generative AI Can Lead to Learning Failures." Art. 100559. Information and Organization 35, no. 1 (March 2025).
- 2025
- Working Paper
Workplace Segregation Between College and Non-college Workers
By: Francis Dillon, Edward L. Glaeser and William Kerr
We measure the level and growth of education segregation in American workplaces from 2000 to 2020.
American workplaces show an educational segregation, measured by the degree to which the establishment
has mostly workers of similar education levels, that is... View Details
Keywords: Isolation; Segregation; Mobility; Learning; Human Capital; Competency and Skills; Demographics
Dillon, Francis, Edward L. Glaeser, and William Kerr. "Workplace Segregation Between College and Non-college Workers." Harvard Business School Working Paper, No. 25-044, March 2025.
- February 2025
- Supplement
Intenseye: Powering Workplace Health and Safety with AI (B)
By: Michael W. Toffel, Shane Greenstein and Sadika El Hariri
Intenseye used its $25 million series A funds to refine and expand its digital safety platform while refining its target markets and ideal customer profile. As the company implemented new approaches to create value for its clients, such as developing an AI-powered... View Details
Keywords: Safety Performance; Occupational Safety; Innovation; Safety; Operations; Health; AI and Machine Learning; Analytics and Data Science; Digital Transformation; Supply Chain Management; Performance Improvement; Entrepreneurship; Product Development; Customer Relationship Management; Value Creation; Venture Capital; Growth and Development Strategy; Information Technology Industry; United States; Europe; Middle East; Turkey
Toffel, Michael W., Shane Greenstein, and Sadika El Hariri. "Intenseye: Powering Workplace Health and Safety with AI (B)." Harvard Business School Supplement 625-025, February 2025.
- 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
- 2025
- Working Paper
Is Love Blind? AI-Powered Trading with Emotional Dividends
By: De-Rong Kong and Daniel Rabetti
We leverage the non-fungible tokens (NFTs) setting to assess the valuation of emotional dividends (LOVE), a long-standing empirical challenge in private-value markets such as art, antiques, and collectibles. Having created and validated our proxy, we use deep learning... View Details
Kong, De-Rong, and Daniel Rabetti. "Is Love Blind? AI-Powered Trading with Emotional Dividends." Working Paper, February 2025.
- February 2025 (Revised April 2025)
- Case
Institutional Neutrality, Restraint or Convenience?
By: Clayton S. Rose, Nicole Zelazko and Alexis Lefort
In the fall of 2023 and winter of 2024, college campuses across the U.S. experienced protests and encampments in the aftermath of the October 7, 2023 terrorist attack on Israel by the Islamist militant group Hamas, and Israel’s subsequent invasion of Gaza. These... View Details
Keywords: Distribution; Cost vs Benefits; Ethics; Governance; Leadership; Crisis Management; Risk Management; Corporate Social Responsibility and Impact; Mission and Purpose; Organizational Change and Adaptation; Organizational Culture; Civil Society or Community; Social Issues; Adaptation; Disruption; Communication Strategy; Higher Education; United States
Rose, Clayton S., Nicole Zelazko, and Alexis Lefort. "Institutional Neutrality, Restraint or Convenience?" Harvard Business School Case 325-022, February 2025. (Revised April 2025.)
- 2025
- Working Paper
Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning
Reinforcement learning (RL) offers potential for optimizing sequences of customer interactions by modeling the relationships
between customer states, company actions, and long-term value. However, its practical implementation often faces significant
challenges.... View Details
Keywords: Dynamic Policy; Deep Reinforcement Learning; Representation Learning; Dynamic Difficulty Adjustment; Latent Variable Models; Customer Relationship Management; Customer Value and Value Chain; Foreign Direct Investment; Analytics and Data Science
Ma, Liangzong, Ta-Wei Huang, Eva Ascarza, and Ayelet Israeli. "Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning." Harvard Business School Working Paper, No. 25-037, February 2025.
- 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
Keywords: AI and Machine Learning; Governing Rules, Regulations, and Reforms; Applications and Software; Well-being
De Freitas, Julian, and I. Glenn Cohen. "Disclosure, Humanizing, and Contextual Vulnerability of Generative AI Chatbots." New England Journal of Medicine AI 2, no. 2 (February 2025).
- January 2025
- Teaching Plan
Knowledge Transfer: Toyota, NUMMI, and GM
By: Willy Shih
Teaching Plan for HBS Case No. 625-003. New United Motors Manufacturing, Inc. (NUMMI) was a joint venture between Toyota and General Motors. It was an opportunity for GM to learn about the Toyota Production System, which was quite different from the mass production... View Details
Keywords: Culture Change; Organizational Culture; Organizational Change and Adaptation; Factories, Labs, and Plants; Joint Ventures; Transformation; Selection and Staffing; Knowledge Acquisition; Knowledge Sharing; Labor Unions; Management Systems; Performance Improvement; Production; Labor and Management Relations; Auto Industry; Japan; United States
- January 2025
- Supplement
Colbún’s Angostura Dam Project (B)
By: James K. Sebenius and Nicolas Andrade
The A case describes Colbún Chile’s plans for the Angostura dam in the Bío Bío River, a hydroelectric construction venture with major challenges given the region’s history of indigenous resistance. This context was especially unfavorable given the highly contentious... View Details