## 6 General Discussion
### Theoretical Implications  
The theoretical implications of this study are multifaceted, offering significant contributions to the growing body of literature on technology acceptance and the integration of AI in human resource management, particularly in the recruitment process. First, the findings from both studies shed light on the perceived advantages and disadvantages associated with the adoption of AI tools by recruiters in their daily tasks. On the one hand, participants highlighted numerous benefits, such as enhanced efficiency, time savings, and the ability to process large volumes of data, which collectively streamline recruitment processes and improve decision-making. On the other hand, the studies also revealed significant concerns, including the potential lack of human touch, biases in algorithms, and ethical considerations, as well as challenges related to reliability and precision. These findings underscore the dual nature of AI adoption in recruitment, demonstrating that while AI tools can enhance operational capabilities, their integration must address critical concerns to ensure a balanced and effective approach to recruitment and selection. Second, by employing the TAM [15] as a theoretical framework, this research provides empirical evidence supporting the role of perceived usefulness and perceived ease of use in shaping recruiters' attitudes and intentions toward adopting AI tools. The findings confirm that these perceptions are pivotal in influencing recruiters' attitudes, which, in turn, foster stronger intentions to use AI tools [16; 56]. This relationship aligns with the core propositions of the TAM, highlighting the importance of how individuals perceive the utility and ease of use of innovations--in this case, AI tools--as critical drivers for motivating their adoption in professional settings. However, while both perceptions are relevant, [PERSON] [41] found that perceived usefulness tends to have a stronger influence on attitude than ease of use. Specifically, in [PERSON]'s study, the regression coefficients indicated that usefulness exerted over four times as much direct influence on attitude as ease of use (0.65 vs. 0.13). Furthermore, perceived ease of use was shown to have a relatively minor direct effect on attitude, instead exerting its influence indirectly through its significant effect on perceived usefulness. [PERSON] [41] explained the predominance of perceived usefulness by noting that it often encapsulates the \"benefits\" and \"costs\" of adopting new technology. In contrast, ease of use reflects the effort required to use the technology [40], which can be viewed more negatively as an additional cost from the user's perspective [56]. This interpretation aligns with previous findings in the literature, such as those of [PERSON] et al. [58], who emphasized that perceptions of usefulness are often the strongest predictor of technology adoption, especially in the context of AL [PERSON] and her colleagues [59] concluded that perceived ease of use plays a smaller role in AI tools adoption, as it pertains primarily to the technical aspects of usage, which have become less critical as users gain more technological familiarity in their daily lives. However, these conclusions do not align with the findings of the present study, where ease of use demonstrates a comparatively higher correlation and variance with attitude. Specifically, the present study reveals different results, with regression coefficients of 0.71 for ease of use and 0.53 for usefulness, suggesting a stronger influence of ease of use in this context. Although [PERSON]'s [41] explanation is valid, a plausible reason for the higher influence of ease of use in the current study may be attributed to the characteristics of the sample. Notably, only 25.1% of the participants are over the age of 41, a demographic more likely to view new technology as challenging and effortful, which may diminish its perceived utility.