ItemArticle

Reimagining Automotive Manufacturing with Generative AI: A Technolology-Organization-Environment Perspective

Title
Reimagining Automotive Manufacturing with Generative AI: A Technolology-Organization-Environment Perspective
Creator
Sivathanu, Brijesh; Pillai, Rajasshrie; Rana, Nripendra P.
Description
Generative AI (Gen-AI) is transforming industries, and the automotive sector is no exception. Auto Component Manufacturing (AutoCM) organizations face strong pressure to adopt Gen-AI for competitiveness, yet little research has examined adoption factors in this context. This study investigates the determinants of Gen-AI adoption in AutoCM firms using the Technology-Organization-Environment framework. A model was developed and tested through survey data from 490 managers, validated via PLS-SEM. The findings reveal key predictors of adoption: perceived intelligence, data quality, absorptive capacity, IT infrastructure, top management commitment, vendor support, competitive pressure, and government support. Results further show that adoption intention drives potential use of Gen-AI, but this relationship is weakened by concerns over Gen-AI hallucination. This research identifies crucial drivers of Gen-AI adoption in AutoCM, extends TOE framework literature, and provides actionable insights for practitioners to strategically harness Gen-AIs transformative potential in the sector. 2025 The Author(s). Published with license by Taylor & Francis Group, LLC.
Source
Journal of Computer Information Systems;
Date
01-01-2025
Publisher
Taylor and Francis Ltd.
Subject
data quality; Generative AI; perceived Gen-AI hallucination potential; PLS-SEM; potential use; TOE
Coverage
Sivathanu B., Christ University, Bangalore, India; Pillai R., Chandragupt Institute of Management Patna, Patna, India; Rana N.P., Queens University Belfast, Belfast, United Kingdom, Humanities and Social Sciences Research Center (HSSRC), Deanship of Scientific Research, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia, College of Business & Economics, University of Johannesburg, Johannesburg, South Africa
Rights
All Open Access; Green Open Access; Hybrid Gold Open Access
Relation
ISSN: 8874417;
Format
online
Language
English
Type
Article

Citation

Sivathanu, Brijesh; Pillai, Rajasshrie; Rana, Nripendra P., “Reimagining Automotive Manufacturing with Generative AI: A Technolology-Organization-Environment Perspective,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/22668.

Output Formats