## 2 Theoretical Framework
### Artificial Intelligence in Recruitment and Selection
The widespread availability of AI tools in recruitment raises important questions regarding recruiters' perceptions of their use, particularly with respect to usability and associated challenges. Several studies have examined both the advantages and disadvantages of incorporating AI tools into recruitment and selection processes [28; 29]. Evidence suggests that AI-powered algorithms are capable of automating a wide range of repetitive, administrative, and time-intensive tasks, particularly those involved in analyzing large volumes of applicant data [19]. These tasks include candidate sourcing, interview scheduling, and processing candidate information. The algorithms are proficient at identifying relevant qualifications and predicting job performance with high accuracy while also reducing the biases that often affect traditional recruitment methods [38]. This automation significantly enhances the efficiency of HR operations by facilitating faster decision-making, shortening time-to-hire, and allowing HR professionals to focus on more strategic tasks, such as identifying the most suitable candidates to meet organizational needs [28]. Additionally, AI tools contribute to improved candidate shortlisting, ensuring that potential hires align more closely with the firm's requirements [25]. In addition to operational efficiencies, AI also significantly elevates the candidate experience by facilitating consistent, transparent, and efficient communication throughout the recruitment process [30]. By ensuring timely updates and engagement, AI-driven solutions contribute to a more seamless and satisfactory journey for candidates, fostering a positive impression of the organization [31]. A recent study by [PERSON] [27] identified three critical factors driving the adoption of AI in HR practices. First, the vast amounts of HR data generated by organizations, such as candidate CVs, necessitate advanced analytical tools capable of processing this data efficiently. Second, AI algorithms' ability to analyze data at a speed and scale beyond human capacity addresses the demand for faster and more accurate decision-making in areas like recruitment. Lastly, the push for AI solutions stems from the need to reduce human subjectivity, minimize biases, and provide tailored recommendations, such as those that are needed when there is the need to choose between diverse candidates, all of which contribute to improving employee experiences and fostering equitable HR practices. However, concerns regarding the adoption of AI in HR persist. A study by Ore and Sposato [32] explored recruiters' perspectives and revealed apprehensions about potential risks associated with AI's reliability and accuracy. Recruiters expressed fears of losing the \"human touch\" in HR processes and raised concerns about the possibility of AI replacing human roles in recruitment. Plus, the use of AI in recruitment and selection also presents a range of ethical, privacy, and legal concerns [30], as well as moral and vilification issues for potential candidates [33]. These ethical considerations are often neglected, with the focus primarily on the operational advantages of AI tools. However, it is critical that AI implementations are aligned with and regulated according to a company's core values and mission to avoid potential negative consequences. Another significant challenge in adopting AI-based recruitment and selection processes is the need for skilled professionals to train the AI systems, ensuring accuracy and reducing errors [31]. For AI systems to be successfully integrated into HR functions, organizations must invest in robust data governance, appropriate AI infrastructure, and comprehensive employee training. Collaboration between HR specialists and AI systems is essential to maximize the potential of these technologies and achieve optimal outcomes [25].