Generative AI in Private Equity for Accumulative Advantage
Name
mahajan-bonny151-lgo-mba-eecs-2025-thesis unsigned.pdf
Description
Thesis PDF
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9.1 MB
Format
Adobe PDF
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772f3d3b0f48e9832e6ee9807097b6cc
Author(s)
Mahajan, Bonny
Advisor(s)
Boning, Duane
Eppinger, Steven
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
Abstract
This research explores the use of Generative AI (Gen AI) for achieving accumulative gains across various business and technical functions within commercial enterprises under private equity firms. While based on applied experiments in a private equity-owned, resource constrained portfolio company, many of the findings presented here may apply in other types of organizations.Through this study, we conduct case studies across key departments such as customer service, purchasing, engineering, employee management, and marketing. For each use case, we delve into the utilization of custom-built or publicly available Gen AI-based tools, aiming to understand the unique considerations and challenges that may arise when implementing Gen AI solutions in industries like manufacturing, which have traditionally been underserved by the tech sector.Through this research, we identify the critical role of humans in the loop, emphasizing the importance of UI/UX design, domain expertise, and local culture in the successful adoption and acceptance of Gen AI tools designed to enhance workforce efficiency in portfolio companies. This study also aims to illustrate how investing in Gen AI technologies is ultimately an investment in a company’s most valuable resource—its employees. By equipping employees with innovative tools, the organization not only improves productivity and job satisfaction but also fosters a culture of continuous improvement and adaptability. This research highlights the transformative potential of Gen AI in reshaping traditional business processes and driving sustainable growth in different functions of organizations.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Sloan School of Management
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