Abstract
Fast-growing technological features of today drive all companies in all sectors to mechanization with automation by Artificial Intelligence (AI). As the maritime and logistics sector moves toward fully digital, AI becomes significant competition element for leading shipping companies in business logistics and maritime nations. Although the use of artificial intelligence requires great investment in the short term, it brings profitability by reducing the costs in the long term. Moreover the environmental regulations of IMO (International Maritime Organization) will hit the maritime industry in 2020 by forcing maritime companies to reduce sulfur content in fuel at 0.5%. From this aspect, using AI will also contribute to reduce ship related carbon emissions by implementing environmentally friendly applications. On the other hand, profitability of seaports will scale up by using emerging technologies that helps accurate forecasts by using scientific innovations related with empty and full container records and their allocations. Moreover, using AI will contribute to the prevention of ship related accidents by anticipating future cases with using pinpoint calculations. Lastly, the basic requirement of implementing sustainable development which is necessary to compete is to follow and implement technological innovations as AI. That’s why this paper researches recent developments and current practices of maritime companies related with AI and shed lights on future studies in terms of shipping companies, maritime workers, governmental authorities and any other rule makers and practitioners.
“Artificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold.”
Ray Kurzweil
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Ceyhun, G.Ç. (2020). Recent Developments of Artificial Intelligence in Business Logistics: A Maritime Industry Case. In: Hacioglu, U. (eds) Digital Business Strategies in Blockchain Ecosystems. Contributions to Management Science. Springer, Cham. https://doi.org/10.1007/978-3-030-29739-8_16
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DOI: https://doi.org/10.1007/978-3-030-29739-8_16
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