Agentic Artificial Intelligence for Port Logistics Optimization: A Secondary Study on Operational Efficiency at Adani Ports

Abstract

Port logistics is a critical component of global trade, yet it continues to face persistent challenges such as congestion, inefficient berth allocation, unpredictable vessel schedules, and poor coordination among stakeholders. This secondary research paper examines the potential of agentic artificial intelligence (AI) in addressing these operational inefficiencies, with a specific focus on Adani Ports and Special Economic Zone (APSEZ), one of India’s largest port operators.
The study is based entirely on secondary data collected from academic journals, industry reports, and existing literature on artificial intelligence, logistics management, and smart port systems. It critically evaluates current technological applications in port logistics, which are largely limited to predictive analytics and decision-support systems, and identifies a significant gap in autonomous decision-making and real-time coordination.
Agentic AI, characterised by multiple autonomous agents capable of independent decision-making and collaboration, is explored as a transformative solution. The research proposes a conceptual framework where AI agents manage key logistics functions such as vessel scheduling, berth allocation, cargo handling, and container yard optimisation. The study also highlights the importance of governance, transparency, and human oversight in deploying such systems within critical infrastructure.
The findings suggest that integrating agentic AI into port operations can significantly reduce vessel turnaround time, enhance resource utilisation, and improve overall operational efficiency. However, successful implementation requires robust governance frameworks to mitigate risks associated with automation. This research contributes to the growing body of knowledge on AI-driven logistics systems and provides strategic insights for the development of intelligent port ecosystems.