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Assessment on the Impact of Artificial Intelligence Driven Supply Chain Software’s in Reducing Shipping Cost in Tanzania

Sharifa Abdulwahid Dayar, Msabaha Juma Mwendapole

Abstract

This study is on the assessment of the impact of Artificial Intelligence (AI)-driven supply chain software on reducing shipping costs in Tanzania, a critical component for enhancing the efficiency and competitiveness of the country’s logistics sector. The study adopts a descriptive research design, utilizing both qualitative and quantitative methods to capture a holistic understanding of the subject matter. A sample of 70 respondents, selected through a combination of random and purposive sampling techniques, provided insights into the current state and future potential of AI in the logistics industry. Key findings reveal that while the adoption rate of AI-driven supply chain software is steadily increasing among Tanzanian logistics firms, driven by the need for enhanced decision-making, cost reduction, and improved demand forecasting, several formidable challenges persist. These challenges include infrastructure deficiencies, regulatory hurdles, a shortage of skilled professionals, and cultural resistance to technological change. Additionally, the study high- lights that AI-driven predictive maintenance and dynamic routing have led to significant cost savings, minimizing unplanned downtime, reducing fuel consumption, and extending vehicle lifespans. Furthermore, the study found that traditional shipping and logistics methods in Tanzania are often hampered by inconsistent infrastructure, particularly in major hubs like Dar es Salaam, where shipping costs can range from $1,500 to $3,000 per container, depending on various factors. In contrast, AI-driven solutions offer real-time optimization, addressing these inefficiencies and contributing to substantial reductions in shipping costs. Based on these findings, the study offers several recommendations. It urges the Tanzanian government to actively promote the economic benefits of AI adoption, including cost savings, operational efficiency, and enhanced global competiti

Keywords

Artificial IntelligenceSupply ChainShipping CostsLogistics AI-driven

References

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