71. Generative AI Meets the Service Sector: A Study Using Topic Modeling
Invited abstract in session TD-38: Foundation Models and Optimization, stream Data Science meets Optimization.
Tuesday, 14:30-16:00Room: Michael Sadler LG19
Authors (first author is the speaker)
| 1. | Arkomita Mukherjee
|
| Information Systems, Indian Institute of Management Kozhikode | |
| 2. | M. P. Sebastian
|
| Information Systems, Indian Institute of Management Kozhikode |
Abstract
Artificial Intelligence (AI) is being increasingly integrated in organizational operations owing to enhanced efficiency, productivity and innovation. Service sectors such as healthcare, banking and education are steadily utilizing AI. Further, AI-powered business processes also enable superior customer services. Generative AI (GenAI) facilitates users to create new content such as text, images or animation based on user inputs in human languages. Following the breakthrough acceptance of GenAI, this study aims to steer forward the emerging discussion surrounding GenAI in services. To address the dearth of studies exploring dominant themes in this particular landscape, we perform natural language processing (NLP) based topic modeling via Latent Dirichlet Allocation (LDA) model. We collect relevant literature comprising of articles and conference proceedings indexed in the Scopus database. We also include suitable publicly available industry reports published by consultancy firms. Our final corpus consists of more than 200 documents. Diverse and meaningful underlying topics are identified which we categorize into overarching themes such as GenAI application in service operations, opportunities, ethical concerns and need for regulations which help provide a holistic view to managers and stakeholders.
Keywords
- Artificial Intelligence
- Service Operations
- Analytics and Data Science
Status: accepted
Back to the list of papers