The article discusses in detail the specific aspects of the organisation of incoming inspection during the construction of facilities in Arctic conditions. Special attention is paid to the unique challenges associated with extreme climatic conditions, remoteness of construction sites and limited time windows for work. These factors significantly complicate traditional methods of quality control of incoming materials, structures, equipment and machinery, which requires new approaches and solutions. The paper identifies information gathering and analysis techniques that form artificial intelligence (AI) models aimed at automating and optimising input inspection processes. These technologies can not only improve the accuracy of inspections and reduce data processing time, but also minimise the impact of the human factor, which can be particularly critical when access to skilled professionals is limited. The authors also look at the potential of AI to predictively analyse and forecast potential defects, enabling early detection of problems and prompt corrective action. The application of AI in the incoming inspection system also helps to reduce overall construction costs by optimising logistics, reducing downtime and increasing resource efficiency. The article provides examples of successful AI implementation at real construction projects in the Arctic region and analyses the effectiveness of the proposed solutions in comparison with traditional quality control methods.