Open Access

REVIEW

Artificial Intelligence Revolutionising the Automotive Sector: A Comprehensive Review of Current Insights, Challenges, and Future Scope

Md Naeem Hossain¹, Md. Abdur Rahim², Md Mustafizur Rahman^1,3,*, Devarajan Ramasamy¹

1 Faculty of Mechanical and Automotive Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, 26600, Malaysia
2 Institute for Intelligent Systems Research and Innovation (ISSRI), Deakin University, Warun Ponds, VIC, 3216, Australia
3 Automotive Engineering Centre, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, 26600, Malaysia

* Corresponding Author: Md Mustafizur Rahman. Email:

(This article belongs to the Special Issue: Artificial Intelligence Current Perspectives and Alternative Paths: From eXplainable AI to Generative AI and Data Visualization Technologies)

Computers, Materials & Continua 2025, 82(3), 3643-3692. https://doi.org/10.32604/cmc.2025.061749

Received 02 December 2024; Accepted 06 February 2025; Issue published 06 March 2025

Abstract

The automotive sector is crucial in modern society, facilitating essential transportation needs across personal, commercial, and logistical domains while significantly contributing to national economic development and employment generation. The transformative impact of Artificial Intelligence (AI) has revolutionised multiple facets of the automotive industry, encompassing intelligent manufacturing processes, diagnostic systems, control mechanisms, supply chain operations, customer service platforms, and traffic management solutions. While extensive research exists on the above aspects of AI applications in automotive contexts, there is a compelling need to synthesise this knowledge comprehensively to guide and inspire future research. This review introduces a novel taxonomic framework that provides a holistic perspective on AI integration into the automotive sector, focusing on next-generation AI methods and their critical implementation aspects. Additionally, the proposed conceptual framework for real-time condition monitoring of electric vehicle subsystems delivers actionable maintenance recommendations to stakeholders, addressing a critical gap in the field. The review highlights that AI has significantly expedited the development of autonomous vehicles regarding navigation, decision-making, and safety features through the use of advanced algorithms and deep learning structures. Furthermore, it identifies advanced driver assistance systems, vehicle health monitoring, and predictive maintenance as the most impactful AI applications, transforming operational safety and maintenance efficiency in modern automotive technologies. The work is beneficial to understanding the various use cases of AI in the different automotive domains, where AI maintains a state-of-the-art for sector-specific applications, providing a strong foundation for meeting Industry 4.0 needs and encouraging AI use among more nascent industry segments. The current work is intended to consolidate previous works while shedding some light on future research directions in promoting further growth of AI-based innovations in the scope of automotive applications.

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Keywords

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