Barriers to AI Adoption in Logistics Management within Manufacturing Industry in Melaka, Malaysia - Tan, Zen Nie; Wan Ahmad, Wan Nurul Karimah (Research in Management of Technology and Business, 2026)
This study examines the barriers to Artificial Intelligence (AI) adoption in logistics management within the manufacturing industry in Malacca, Malaysia. Although AI has been widely recognized for its potential to enhance operational efficiency, improve decision-making, and optimize supply chain performance, its adoption in logistics operations remains relatively low, particularly among manufacturing firms. This research aims to identify and analyze the key barriers hindering AI adoption, focusing on organizational resistance to change, cybersecurity and data privacy concerns, and high implementation costs. A quantitative research approach was employed, utilizing survey questionnaires distributed to manufacturing companies in Malacca. The collected data were analyzed using Statistical Package for the Social Sciences (SPSS) to examine the relationships between identified barriers and the level of AI adoption. The findings indicate that high initial investment costs, resistance to organizational change among employees, and concerns regarding data security and privacy are the most significant obstacles to AI implementation. Additionally, a lack of technical expertise and limited awareness of AI benefits further impede adoption. The study concludes that addressing these challenges through targeted government incentives, workforce upskilling programs, enhanced cybersecurity frameworks, and stronger organizational support is essential to promote AI integration. The findings provide valuable insights for policymakers, industry practitioners, and manufacturing firms in developing effective strategies to accelerate AI adoption and improve logistics performance in Malacca’s manufacturing sector.