Forthcoming Articles

International Journal of Automotive Technology and Management

International Journal of Automotive Technology and Management (IJATM)

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International Journal of Automotive Technology and Management (One paper in press)

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  • AI drivers and barriers in the automotive industry: an interview study   Order a copy of this article
    by Clarissa Amico, Gianluca Martin, Nizar Abdelkafi, Roberto Cigolini, Gianluca Tedaldi 
    Abstract: While extensive research has explored artificial intelligence (AI) drivers and barriers broadly, only a few studies dealt with the automotive sector. This study examines the drivers and barriers to AI adoption in this industry. Using a qualitative approach, we conducted semi-structured interviews with 24 industry experts. The interview data were analysed and coded to identify drivers and barriers. AI adoption is driven by positive expectations, technical and economic benefits, and successful use cases, while barriers stem from resource constraints, stakeholder concerns, and project complexity. Companies can maximise AIs potential by managing expectations, investing in skilled talent, and breaking down complex projects into manageable steps. Additionally, transparency, trust, and regulatory compliance are crucial for overcoming scepticism and ensuring successful implementation. This study contributes to the AI literature in the automotive sector. Practitioners can leverage these findings to enhance AI adoption by minimising risks and boosting operational effectiveness.
    Keywords: artificial intelligence; automotive industry; drivers and barriers; experts interview; TOE framework.
    DOI: 10.1504/IJATM.2026.10081168
     

 

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