%0 Journal Article
%A Ljulj, Andrija
%A Štambuk, Igor
%A Slapničar, Vedran
%T Integrating Artificial Intelligence into Naval Capability Development
%J TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation
%V 20
%N 1
%P 173-185
%D 2026
%U ./Article_Integrating_Artificial_Intelligence_Ljulj,77,1649.html
%X The rapid advancement of artificial intelligence (AI) is transforming naval capabilities, reshaping ship design, lifecycle management, operational decision-making, and autonomous maritime systems. Naval platforms are among the most complex engineered systems, characterised by long service lives, safety-critical functions, and demanding operational environments, making AI integration both strategically attractive and technically challenging. This paper presents an engineering-oriented review of AI applications in the naval domain, focusing on their role across the capability development lifecycle. To illustrate practical implementation, a Random Forest regression model is developed to support early-stage prediction of the block coefficient of naval ships. The review highlights significant opportunities associated with AI integration, including enhanced decision-making, improved design efficiency, and increased operational effectiveness. However, successful AI adoption requires technological advancement alongside organisational adaptation, strong governance, and sustained investment in human expertise. AI should therefore be understood not as a replacement for naval engineering expertise, but as a force multiplier that augments analytical capacity and accelerates innovation across the maritime domain.
%@ 2083-6473
%R 10.12716/1001.20.01.19