Key points are not available for this paper at this time.
Objective: This study aims to comprehend the current state of integration between artificial intelligence (AI) and the human resources (HR) sector. Specifically, it investigates the implementation of AI in HR, explores the challenges associated with this integration, and examines potential hazards related to data usage, AI's perceived gimmickry, and algorithmic governance. Method: Employing a descriptive research design, this study relies on secondary data as no primary research was conducted. Information was collected from research papers, books, websites, blogs on human resources, and survey reports released by various research groups. Results: The analysis reveals that AI's adoption in the HR sector is still in its early stages despite significant advancements made by start-ups. Challenges stem from various factors, including data complexities, the risk of AI being seen as a mere gimmick, and concerns about algorithmic governance. The multifaceted nature of AI introduces diverse approaches and applications, from algorithms to deep learning and natural language processing. The study also differentiates between strong AI (general intelligence) and weak AI (problem-specific intelligence). The study emphasizes that HR is a pivotal element of any business, directly impacting employee well-being, communication, and productivity. The integration of AI has brought notable improvements by automating low-value HR tasks, freeing resources for strategic work. AI's capacity to analyze vast data volumes rapidly promises enhanced employee experiences across talent management and recruitment. Conclusions: In conclusion, AI's integration into the HR sector is still evolving, with both promise and challenges. The study underscores the need for addressing the complexities of data utilization, avoiding AI's reduction to mere gimmickry, and establishing responsible algorithmic governance. By understanding the nuances of AI integration in HR, organizations can leverage its potential to enhance productivity, communication, and employee experiences.
Kaur et al. (Mon,) studied this question.