Assessing the Impact of Large Language Models on Five Functional Areas within Companies

Details

Supervisors

Lejeune, Christophe

Faculty

Louvain School of Management

Degree label

Master [120] en sciences de gestion, à finalité spécialisée

Abstract

This thesis explores the transformative impact of Large Language Models (LLMs) within five functional areas : finance and accounting, marketing and sales, human resources, IT operations, and operations management. Grounded in an extensive literature review, the research delves into the historical development of LLMs, their key components, and diverse types, alongside a methodical analysis of their integration, implications and limitations in business environments. Employing an exploratory research approach through structured interviews with 26 professionals across the different functional areas, this study evaluates LLMs’ impact on performance. Results indicate that LLMs substantially optimize time and resource allocation, enhance accuracy in data processing, and foster innovation by automating routine tasks, thus allowing professionals to focus on more strategic activities. However, the thesis also identifies potential risks, including over-reliance on automated systems and concerns regarding data privacy and security. Overall, this thesis contributes to a nuanced understanding of LLMs' functional impact on organizational performance and outlines a future research agenda to further explore this emerging field.