Integrating Target Costing and Artificial Intelligence: A Strategic Framework for Enhancing Operational Efficiency in the Air Transport Sector – A Case Study of Iraqi Airways

Abstract

This research aims to study the impact of integrating strategic cost management with artificial intelligence (AI) technologies on enhancing operational efficiency and reducing operating costs in the air transport sector, focusing on Iraqi Airways as a case study. The research employed a descriptive, analytical, and comparative approach, reviewing relevant literature and analyzing financial and operational data for long-haul flights, such as the Baghdad-Moscow-Baghdad route. The results showed that applying the target costing concept provides a proactive tool for determining acceptable costs and improving resource management, while AI enhances demand forecasting accuracy, supports dynamic pricing, and enables more effective fuel and crew management. The study also demonstrated that integrating target costing with AI technologies contributes to improved operational planning, reduced waste, and competitive pricing, in addition to supporting data-driven strategic decision-making. This positively impacts the company's financial performance and enhances its competitiveness. Furthermore, the research highlights the importance of adopting AI models within the target costing framework, with a focus on training personnel to utilize these models to maximize resource efficiency, enhance effective pricing capabilities, and achieve sustainable operational efficiency. The research presents an integrated framework for supporting sustainable competitiveness in the air transport sector.