AI-driven climate resilience in maritime ports: opportunities and challenges

Mohamed Nabil Elnabawi, Elsonosi Balbaa, Said Abd Elkader

Abstract


Purpose: The global maritime sector faces two simultaneous pressures — the obligation to reduce carbon emissions and the adaptation to climate change acceleration. Traditional operating models have become insufficient to confront these new challenges. This paper explores how Artificial Intelligence (AI) can support the capabilities of the maritime sector to face climate change.

Design/Methodology/Approach: This paper presents a thematic review of academic literature, international reports and industry publications on AI applications in the maritime field for the period 2019-2026, focusing on three main dimensions: emissions reduction, port operations and climate resilience.

Findings: This review reveals the AI real contribution in supporting climate change resilience throughout the predictive maintenance, enhancing ship's routing and Just-In-Time (JIT) as well as digital twins, however this effect remains subjected by the operational integrations and stakeholders' readiness as well as clear governance framework.

Research implications: This study fills a long-standing gap where AI and sustainability in maritime are spoken of in tandem with little thought to how they interplay in the real world.

Practical implications: The findings provide practical guidance for port operators and policymakers to effectively apply AI in facing climate challenges, particularly in developing ports.

Originality: The paper presents a comprehensive thematic review on AI applications in maritime ports, through collecting evident from various fields in order to identify the main challenges and trend forecasting in future research.

Keywords: Artificial Intelligence, Climate Resilience, GHG Emissions, Just-in-Time, Predictive Maintenance, Smart Ports

 

Received: 18 July 2026

Accepted: 26 September 2026

Published: 01 October 2026


Keywords


Artificial Intelligence, Climate Resilience, GHG Emissions, Just-in-Time, Predictive Maintenance, Smart Ports

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DOI: https://doi.org/10.21622/MRT.2026.05.2.2327

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Copyright (c) 2026 Mohamed Nabil El Nabawi, Elsonosi Balbaa, Said Abd Elkader

Maritime Research and Technology

E-ISSN: 2812-5622

P-ISSN: 2812-5614

 

Published by:

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Arab Academy for Science, Technology and Maritime Transport (AASTMT)

Alexandria, Egypt

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