AI-driven vehicle customization and personalization in automobile industry

The automobile industry is experiencing a profound digital transformation with artificial intelligence emerging as a cornerstone technology reshaping customer experiences and operational paradigms. AI-powered vehicle selection and configuration systems represent transformative applications revolutionizing how consumers discover, personalize, and purchase vehicles. Modern automotive manufacturers leverage sophisticated data analytics platforms like SAP HANA, with in-memory computing capabilities processing configuration variables during real-time customer interactions. These systems analyze substantial volumes of customer data to deliver highly personalized vehicle configurations tailored to individual preferences, driving habits, and lifestyle requirements. The technological foundation incorporates machine learning, natural language processing, and big data analytics within unified customer data platforms, enabling remarkable improvements in customization accuracy and delivery timelines. The implementation methodologies span hyper-personalized vehicle configuration, dynamic pricing optimization, and fleet electrification strategies, resulting in significant operational efficiency improvements, customer experience enhancements, and sustainability impacts. Future directions include blockchain-verified vehicle customization, advanced AI methodologies, and integration of extended reality, promising to further revolutionize the automotive customization landscape through immutable configuration records, reinforcement learning models, and immersive configuration experiences.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-06-06
DOI
https://doi.org/10.30574/wjaets.2025.15.3.0921
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-driven vehicle customization and personalization in automobile industry

Venkateswaran Petchiappan
1 links
World Journal of Advanced Engineering Technology and Sciences
Manufacturing Process and Optimization
article

AI-driven vehicle customization and personalization in automobile industry

Venkateswaran Petchiappan
article en

Abstract

The automobile industry is experiencing a profound digital transformation with artificial intelligence emerging as a cornerstone technology reshaping customer experiences and operational paradigms. AI-powered vehicle selection and configuration systems represent transformative applications revolutionizing how consumers discover, personalize, and purchase vehicles. Modern automotive manufacturers leverage sophisticated data analytics platforms like SAP HANA, with in-memory computing capabilities processing configuration variables during real-time customer interactions. These systems analyze substantial volumes of customer data to deliver highly personalized vehicle configurations tailored to individual preferences, driving habits, and lifestyle requirements. The technological foundation incorporates machine learning, natural language processing, and big data analytics within unified customer data platforms, enabling remarkable improvements in customization accuracy and delivery timelines. The implementation methodologies span hyper-personalized vehicle configuration, dynamic pricing optimization, and fleet electrification strategies, resulting in significant operational efficiency improvements, customer experience enhancements, and sustainability impacts. Future directions include blockchain-verified vehicle customization, advanced AI methodologies, and integration of extended reality, promising to further revolutionize the automotive customization landscape through immutable configuration records, reinforcement learning models, and immersive configuration experiences.

World Journal of Advanced Engineering Technology and SciencesVol. 15(3)
Openalex Percentile: Top 82%
Manufacturing Process and Optimization
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AI-driven vehicle customization and personalization in automobile industry — Venkateswaran Petchiappan · World Journal of Advanced Engineering Technology and Sciences (2025) | TGRS Research Map | TGRS