## 2 Theoretical Framework
### Artificial Intelligence in Recruitment and Selection  
The recruitment and selection process traditionally consists of three stages: sourcing, screening, and selecting [26]. However, the methods employed throughout these stages have undergone significant transformations over time, particularly with the automation and adoption of AI tools in various recruitment and selection activities. The use of AI in recruitment begins with the sourcing phase, which is aimed at attracting external candidates for potential vacancies [27]. In this stage, recruiters have acknowledged that AI can significantly enhance efficiency and effectiveness [28]. For instance, the use of AI eliminates the need for complex Boolean search strings, allowing recruiters to allocate more time and focus on subsequent stages of the recruitment process. Currently, sourcing often involves AI tools like interactive chatbots or automated answering systems, which assist in addressing minor inquiries, such as questions about job descriptions [26]. AI-driven chatbots and virtual assistants are particularly useful in managing high-volume tasks by providing instant responses to queries, scheduling interviews, and organizing responsibilities [29; 30; 31]. This not only improves response times but also enhances employee satisfaction [25; 32]. Additionally, recruiting chatbots can engage potential candidates by informing them about job opportunities and fostering improved communication between companies and applicants [33]. Despite these advantages, AI tools have limitations, particularly in evaluating soft skills or other intangible qualities, which remain challenging for current systems [34]. Following the sourcing phase, the screening phase involves reviewing candidates' resumes, increasingly with the assistance of AI tools alongside HR professionals [35]. This process begins with an assessment of whether the candidate's qualifications match the requirements of the open position. AI algorithms are then employed to analyze resumes against predetermined criteria to identify the most suitable applicants [24]. Through machine learning, candidate matching systems can sift through large datasets, streamlining the process of selecting the best-fit candidates [33]. An example of such an AI tool is Ideal, which assists in screening resumes and shortlisting candidates based on job-specific criteria. Many recruiters predict that the role of HR specialists in the screening process will diminish over time, with AI systems eventually taking full responsibility for resume evaluation [34]. The rapid adoption of AI in screening procedures has led to an increased focus on efficiently assessing candidates' competencies [27]. This shift highlights the growing reliance on AI to automate and optimize the screening process, ensuring a faster and more accurate selection of candidates. In the selection phase, the recruiter chooses the most suitable candidates from the pool of applicants based on predefined criteria. While AI tools play a significant role in assisting with candidate evaluation, the final selection decision remains with HR professionals. This decision is typically based on a combination of personal interviews, resume assessments conducted by either AI or HR and, for certain roles, group assessments [35]. An emerging AI-based method in the selection process is \"video interview analysis\", which uses algorithms for facial recognition and natural language processing to evaluate candidates. These AI tools analyze non-verbal cues such as body language and emotional expressions, helping recruiters assess communication skills more effectively [36]. Tools like HireValue analyze both verbal and non-verbal cues, while RecRight offers a video interviewing platform with AI capabilities for evaluating candidates' communication skills and cultural fit [37]. InterviewBuddy Pro, another AI-driven tool, aids in interview preparation by providing feedback and insights for improvement.