## 2 Theoretical Framework
### Intention to Use AI Tools in Recruitment and Selection  
Previous literature highlighted that psychosocial factors play a central role in the acceptance of AI technology. Acceptance-related variables such as perceived usefulness, perceived ease of use and attitude have all been found to significantly and positively predict behavioral intention, willingness, and actual use of AI technology [39].  
[PERSON] developed the TAM in the 1980s to explore how users adopt information systems, particularly in the context of new technologies. TAM was the first to highlight the psychological factors influencing technology acceptance, and it is rooted in the Theory of Reasoned Action formulated by [PERSON] [40].  
Originally, TAM was designed to assess the impact of four internal variables on \"actual use\", which refers to real, effective engagement with the technology, such as AI tools [15]. The key factors influencing this actual use are the intention to use, which is shaped by the perceptions of perceived usefulness and ease of use, and the user's attitude toward using the technology. Perceived usefulness is defined as the degree to which a person believes that using a particular system would enhance his or her job performance [41]. For instance, in the context of AI tools, perceived usefulness may relate to improved decision-making accuracy, automation of routine tasks, or enhanced productivity. Perceived ease of use, on the other hand, refers to the \"degree to which a person believes that using a particular system would be free of effort\" [40] (p. 320). This aspect underscores the cognitive and physical effort associated with learning and operating the technology. Systems perceived as intuitive and user-friendly are more likely to foster positive attitudes and subsequent adoption. These two constructs influence a user's attitude toward technology, which in turn affects their intention to adopt it [15]. A positive attitude reflects favorable feelings and a willingness to engage with the system, whereas a negative attitude can hinder adoption. Crucially, attitude serves as a mediator, bridging the relationship between the perceived characteristics of the technology and the user's intention to use it [40].  
Despite being one of the oldest models, TAM remains the most widely used framework for measuring technology acceptance. It has demonstrated high success rates in predicting behavioral intentions and is regarded as the preferred choice for evaluating technology acceptance across various contexts [16; 17; 18]. One of the reasons for its widespread use is its ability to incorporate additional variables, which allows for more flexibility and precision in diverse settings [39]. TAM is also favored for its simplicity, ease of use, and low cost, making it an effective tool for gathering general data on individuals' perceptions of technology [42]. This makes TAM an ideal model for understanding how users adopt and engage with new technologies, including AI tools, in HR contexts [19].  
Thus, based on the TAM, it is posited that perceived ease of use and perceived usefulness will shape recruiters' intentions to adopt AI tools in recruitment and selection, primarily through their impact on recruiters' attitudes toward AI (see Figure 1). Considering this, we formulate the following research question: How do recruiters perceive AI tools in terms of their advantages and disadvantages, and will this perceptiveness subsequently affect the intention to use AI tools in recruitment and selection processes?  
Additionally, the following hypothesis was also formulated:  
**Hypothesis 1**.: _(a) Perceived ease of use and (b) perceived usefulness will influence recruiters' intentions to adopt AI tools through their attitudes toward such tools._