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  • All HBS Web  (1,220)
    • People  (1)
    • News  (247)
    • Research  (701)
    • Events  (17)
    • Multimedia  (9)
  • Faculty Publications  (585)
← Page 9 of 1,220 Results →
  • May 2025
  • Teaching Note

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

By: Tsedal Neeley
Teaching Note for HBS Case No. 425-720. Florian Hillen, co-founder and CEO of VideaHealth, a startup using artificial intelligence (AI) to detect dental conditions on x-rays, spent the early years of his company laying the groundwork for an AI factory. This AI factory,... View Details
Keywords: Diagnostics; Organization Design; Change Management; Disruption; Transformation; Health Care and Treatment; AI and Machine Learning; Technological Innovation; Technology Adoption; Management Style; Organizational Culture; Success; Technology Industry; Health Industry; United States
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Neeley, Tsedal. "The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation." Harvard Business School Teaching Note 425-102, May 2025.
  • September 2024 (Revised January 2025)
  • Exercise

Building an AI First Snack Company: A Hands-on Generative AI Exercise

By: Iavor I. Bojinov
Although the term 'Generative AI' (GenAI) is widely recognized, its practical application in daily workflows has yet to be understood. This exercise introduces students to GenAI tools, demonstrating how they can be seamlessly integrated into professional work practices... View Details
Keywords: AI and Machine Learning; Technology Adoption; Marketing Strategy; Product Launch; Brands and Branding
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Bojinov, Iavor I. "Building an AI First Snack Company: A Hands-on Generative AI Exercise." Harvard Business School Exercise 625-052, September 2024. (Revised January 2025.)
  • November–December 2023
  • Article

Keep Your AI Projects on Track

By: Iavor Bojinov
AI—and especially its newest star, generative AI—is today a central theme in corporate boardrooms, leadership discussions, and casual exchanges among employees eager to supercharge their productivity. Sadly, beneath the aspirational headlines and tantalizing potential... View Details
Keywords: Generative Models; AI and Machine Learning; Success; Failure; Product Development; Technology Adoption
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Bojinov, Iavor. "Keep Your AI Projects on Track." Harvard Business Review 101, no. 6 (November–December 2023): 53–59.
  • Article

Oracle Efficient Private Non-Convex Optimization

By: Seth Neel, Aaron Leon Roth, Giuseppe Vietri and Zhiwei Steven Wu
One of the most effective algorithms for differentially private learning and optimization is objective perturbation. This technique augments a given optimization problem (e.g. deriving from an ERM problem) with a random linear term, and then exactly solves it.... View Details
Keywords: Machine Learning; Algorithms; Objective Perturbation; Mathematical Methods
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Neel, Seth, Aaron Leon Roth, Giuseppe Vietri, and Zhiwei Steven Wu. "Oracle Efficient Private Non-Convex Optimization." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020).
  • 18 Apr 2000
  • Research & Ideas

Learning in Action

Bean, the U.S. Army's Center for Army Lessons Learned (CALL), AT&T's Bell Laboratories, the Timken Companies and General Electric's Change Acceleration Process (CAP).   L.L. Bean has long relied on... View Details
Keywords: by David A. Garvin
  • 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
Keywords: AI and Machine Learning; Behavior; Time Management
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Dillon, Eleanor W., Sonia Jaffe, Nicole Immorlica, and Christopher T. Stanton. "Shifting Work Patterns with Generative AI." NBER Working Paper Series, No. 33795, May 2025. (Conditionally Accepted at American Economic Review: Insights .)
  • June 2024
  • Teaching Note

Beamery: Using Skills and AI to Modernize HR

By: Boris Groysberg, David Lane, Susan Pinckney and Alexis Lefort
Teaching Note for HBS Case No. 424-004. Unicorn human relationships startup Beamery evaluates it growth versus depth strategy as its strategic partners and customers could become future competitors in a quickly changing AI based human resources and talent management... View Details
Keywords: Analysis; Business Growth and Maturation; Business Model; Business Startups; Business Plan; Disruption; Transformation; Talent and Talent Management; Decisions; Diversity; Ethnicity; Gender; Nationality; Race; Residency; Higher Education; Learning; Entrepreneurship; Fairness; Cross-Cultural and Cross-Border Issues; Global Strategy; Growth and Development; AI and Machine Learning; Digital Platforms; Disruptive Innovation; Technological Innovation; Job Offer; Job Search; Knowledge Acquisition; Knowledge Use and Leverage; Product; Mission and Purpose; Strategic Planning; Problems and Challenges; Corporate Strategy; Equality and Inequality; Valuation; Value Creation; Employment Industry; United Kingdom
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Groysberg, Boris, David Lane, Susan Pinckney, and Alexis Lefort. "Beamery: Using Skills and AI to Modernize HR." Harvard Business School Teaching Note 424-072, June 2024.
  • Web

What an Army Commander Learned About Using AI to Combat Cyberattacks | Working Knowledge

because it was slower and potentially more dangerous than having AI on our side. The lessons we learned from this simulation certainly don’t apply only to the military.... View Details
  • 2022
  • Working Paper

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective

By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju
As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how... View Details
Keywords: AI and Machine Learning; Analytics and Data Science; Mathematical Methods
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Krishna, Satyapriya, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Working Paper, 2022.
  • April 2024
  • Article

Detecting Routines: Applications to Ridesharing CRM

By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal... View Details
Keywords: Ride-sharing; Routine; Machine Learning; Customer Relationship Management; Consumer Behavior; Segmentation
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Dew, Ryan, Eva Ascarza, Oded Netzer, and Nachum Sicherman. "Detecting Routines: Applications to Ridesharing CRM." Journal of Marketing Research (JMR) 61, no. 2 (April 2024): 368–392.
  • April 2017
  • Case

The Future of Patent Examination at the USPTO

By: Prithwiraj Choudhury, Tarun Khanna and Sarah Mehta
The U.S. Patent and Trademark Office (USPTO) is the federal government agency responsible for evaluating and granting patents and trademarks. In 2015, the USPTO employed approximately 8,000 patent examiners who granted nearly 300,000 patents to inventors. As of April... View Details
Keywords: Machine Learning; Telework; Collaborating With Unions; Human Resources; Recruitment; Retention; Intellectual Property; Copyright; Patents; Trademarks; Knowledge Sharing; Technology Adoption; Organizational Change and Adaptation; Performance Productivity; Performance Improvement; District of Columbia
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Choudhury, Prithwiraj, Tarun Khanna, and Sarah Mehta. "The Future of Patent Examination at the USPTO." Harvard Business School Case 617-027, April 2017.
  • November 2023 (Revised April 2024)
  • Case

Khanmigo: Revolutionizing Learning with GenAI

By: William A. Sahlman, Allison M. Ciechanover and Emily Grandjean
Already a leader in the edtech space since its 2008 launch, Khan Academy was now one of the first edtech organizations to embrace generative artificial intelligence ("genAI"). In March 2023, Khan Academy began beta testing Khanmigo, a genAI “guide” and tutor built with... View Details
Keywords: Technology Adoption; Leading Change; Entrepreneurship; Risk and Uncertainty; Education; AI and Machine Learning; Corporate Social Responsibility and Impact; Education Industry; Technology Industry; United States; San Francisco
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Sahlman, William A., Allison M. Ciechanover, and Emily Grandjean. "Khanmigo: Revolutionizing Learning with GenAI." Harvard Business School Case 824-059, November 2023. (Revised April 2024.)
  • 18–19 Nov 2022
  • HBS Alumni Events

D^3 Catalyst: Building AI Companies

The Building AI Companies D^3 Catalyst Program is focused on the opportunities and challenges created by the digital transformation of our economy, and the emergence of digital networks and artificial intelligence (AI) as a foundation of the modern organization - both... View Details
  • June 2024
  • Case

Aidoc: Building a Hospital-Centric AI Platform

By: Ariel D. Stern and Susan Pinckney
In 2023, Israel-based AI health care company Aidoc evaluated its future. The company, founded in 2016, had grown from commercializing a single AI product for radiologists to a software platform that could detect 20 conditions and immediately notify care teams of... View Details
Keywords: Business Growth and Maturation; Business Model; Business Organization; Business Startups; Disruption; Cost vs Benefits; Decision Choices and Conditions; Decisions; Private Sector; Entrepreneurial Finance; Global Range; Global Strategy; Globalized Markets and Industries; Governance Compliance; Governance Controls; Governing and Advisory Boards; Policy; Medical Specialties; AI and Machine Learning; Digital Platforms; Digital Transformation; Technology Adoption; Disruptive Innovation; Innovation and Management; Innovation Strategy; Laws and Statutes; Growth and Development Strategy; Growth Management; Distribution; Product Development; Success; Performance Efficiency; Strategic Planning; Research and Development; Risk and Uncertainty; Business Strategy; Competitive Advantage; Value Creation; Health Industry; Israel
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Stern, Ariel D., and Susan Pinckney. "Aidoc: Building a Hospital-Centric AI Platform." Harvard Business School Case 624-046, June 2024.
  • 2024
  • Article

Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules

By: Michael Lingzhi Li and Kosuke Imai
A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today’s scientists across... View Details
Keywords: AI and Machine Learning; Research
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Li, Michael Lingzhi, and Kosuke Imai. "Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules." Journal of Causal Inference 12, no. 1 (2024).
  • 01 Jun 2024
  • News

Leveraging Generative AI

Four decades after HBS became the first business school in the country to require the use of personal computers in the MBA Program, the School is undergoing a different kind of technological transformation, one that leverages generative artificial intelligence (GenAI)... View Details
Keywords: Jennifer Gillespie
  • December 1, 2021
  • Article

Do You Know How Your Teams Get Work Done?

By: Rohan Narayana Murty, Rajath B. Das, Scott Duke Kominers, Arjun Narayan, Suraj Srinivasan, Tarun Khanna and Kartik Hosanagar
In a research study at four Fortune 500 companies, when managers were asked about their teams’ work, on average they either did not know or could not remember 60% of the work their teams do. This is a major problem because it can lead to unrealistic digital... View Details
Keywords: Leading Teams; Work Recall Gap; Machine Learning; Algorithms; Groups and Teams; Management; Technological Innovation
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Murty, Rohan Narayana, Rajath B. Das, Scott Duke Kominers, Arjun Narayan, Suraj Srinivasan, Tarun Khanna, and Kartik Hosanagar. "Do You Know How Your Teams Get Work Done?" Harvard Business Review Digital Articles (December 1, 2021).
  • October 2021 (Revised September 2022)
  • Case

SmartOne: Building an AI Data Business

By: Karim R. Lakhani, Pippa Armerding, Gamze Yucaoglu and Fares Khrais
The case opens in August 2021, as Habib and Shahysta Hassim, husband and wife co-founders of the data labeling company SmartOne, contemplate the strategy of the high growth company. Between 2016 and 2021, SmartOne had kept doubling its size every two years and now,... View Details
Keywords: Artificial Intelligence; Data Labeling; Entrepreneurship; Strategy; Operations; Business Model; Growth Management; Growth and Development Strategy; AI and Machine Learning; Africa; Madagascar; Europe; France; United States
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Lakhani, Karim R., Pippa Armerding, Gamze Yucaoglu, and Fares Khrais. "SmartOne: Building an AI Data Business." Harvard Business School Case 622-059, October 2021. (Revised September 2022.)
  • September 2023 (Revised April 2024)
  • Case

Atomwise: Strategic Opportunities in AI for Pharma

By: Satish Tadikonda
Abraham Heifets and his co-founder, Izhar Wallach, had founded Atomwise to develop i) an AI engine to transform drug discovery by creating better medicines faster, and ii) a machine learning-based discovery engine that combined the power of convolutional neural... View Details
Keywords: Business Model; Business Startups; AI and Machine Learning; Science-Based Business; Technological Innovation; Biotechnology Industry; Pharmaceutical Industry
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Tadikonda, Satish. "Atomwise: Strategic Opportunities in AI for Pharma." Harvard Business School Case 824-043, September 2023. (Revised April 2024.)
  • 2025
  • Working Paper

Narrative AI and the Human-AI Oversight Paradox in Evaluating Early-Stage Innovations

By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang
Do AI-generated narrative explanations enhance human oversight or diminish it? We investigate this question through a field experiment with 228 evaluators screening 48 early-stage innovations under three conditions: human-only, black-box AI recommendations without... View Details
Keywords: Large Language Models; AI and Machine Learning; Innovation and Invention; Decision Making
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Lane, Jacqueline N., Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh, and Pei-Hsin Wang. "Narrative AI and the Human-AI Oversight Paradox in Evaluating Early-Stage Innovations." Harvard Business School Working Paper, No. 25-001, August 2024. (Revised May 2025.)
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