## 2 Literature Review
### The Use of AI in Handover, Commissioning, and Warranty Period  
After project completion, the project is handed over to the end user, with all systems tested, commissioned, and provided with warranties for all materials. Introducing AI into this phase can streamline processes, reduce costs, and enhance quality. In [37], the authors address challenges in the handover process, such as post-construction defects, poor information fidelity, and the interoperability of BIM and Facility Management systems. Their research highlights the need to improve handover practices and formalize information requirements for better sustainability outcomes. Moreover, according to [24], for the purpose of handover, there are several key information categories where AI tools demonstrate their value in enhancing the process, such as specifications, equipment location, maintenance instructions, and warranty certificates. In addition, several studies such as those by [24; 38], identify specific challenges related to building handover, operations, and maintenance. These challenges include managing  
Figure 5: Application Areas of AI in Project Management [33]. asset information, as-built design drawings, and maintenance details for each system. They emphasize the importance of proper asset information, including dates, system manuals, and maintenance records. To address these challenges, refs. [39; 40] propose using asset information management and BIM tools to ensure better management of warranties and maintenance processes. In view of the above, several studies, such as those in [41; 42; 43; 44; 45] highlight the widespread adoption of AI across various industries like healthcare, finance, and business. These studies demonstrate the substantial social and economic benefits of AI applications, emphasizing its transformative potential. The growing use of AI in these sectors stresses the importance of integrating AI into aviation construction projects, project management, and throughout the project lifecycle to drive innovation, improve outcomes, and enhance overall performance. Nevertheless, while AI offers numerous advantages, there are several challenges specific to the aviation industry, particularly in aviation construction projects. Table 1 illustrates some of the advantages and disadvantages of using AI, specifically within the construction field [1]. Currently, AI is serving as a transformative force across various industries, and it is crucial to fully understand both its benefits and drawbacks in order to optimize its potential and decision-making capabilities effectively. While many of the advantages have already been discussed earlier in the paper, the following outlines some of the challenges faced, especially in the context of the aviation industry. * **High implementation costs** In recent times, it has become clear that the scale of construction projects is continually changing and evolving. The introduction of new technologies and the integration of AI tools within services involves significant costs, including infrastructure setup, technology acquisition, development expenses, and ongoing maintenance requirements [18]. According to [21], the high costs associated with these technologies can be justified by demonstrating their long-term benefits, such as reduced construction time, lower operational costs, and an improved approach to sustainability.