CHAPTER ONE
INTRODUCTION
1.1 Background of the Study
In today's interconnected world, the conventional methods of conducting business are being questioned. The competition is no longer limited to local firms, but rather organizations must consistently compete on a global scale due to the shrinking effect of new technologies (Erixon, 2018). Consequently, to remain current and maintain a competitive edge, it is essential for organizations to embrace these technological advancements.
Every organization aims to address a problem by offering products, services, or both. This objective defines the mission, vision, and values of an organization. To achieve this, human labor is necessary. Humans serve as a valuable source of knowledge and expertise that every organization can and should tap into. Therefore, the recruitment and retention of such employees play a significant role in today's context (De Kok and Uhlaner, 2001). However, Human Resource Management (HRM) plays a vital role in ensuring that organizations acquire and retain the right talent to drive their success.
Human resource management (HRM) encompasses the activities of hiring, training, compensating, creating policies for, and formulating strategies to retain employees. Over the past two decades, HRM has experienced significant transformations, leading to its heightened significance in today's organizations (University of Minnesota, 2023). Traditionally, HRM procedures like recruitment, employee training, and development have been both time-consuming and labor-intensive. Specifically, the recruitment process involves sifting through numerous resumes, conducting interviews, and making subjective judgments based on limited information. These processes not only suffer from inefficiencies but also carry the risk of biases that can result in erroneous hiring decisions.
The emergence of technology has revolutionized HR processes. Organizations have embraced artificial intelligence (AI) to streamline recruitment procedures, enabling them to efficiently and impartially identify the most competent candidates within a specified timeframe and budget (Yu-Shen et al.,2020). Within the management discourse, there has been a significant progression from big data (BD) to machine learning (ML) and ultimately to artificial intelligence (AI) (Tambe et al., 2018).
Artificial intelligence entails the replication of human intelligence processes by machines, specifically computer systems. As defined by Kaplan and Haenlein (2019), AI is characterized by a system's capacity to accurately comprehend external input, acquire knowledge from it, and employ that knowledge to accomplish specific performance objectives through adaptive adjustments. AI encompasses a range of applications, including expert systems, natural language processing, speech recognition, and machine vision.
AI encompasses a wide array of technologies and academic disciplines that have been in existence for many years. However, it is only recently that they have become practical and viable for implementation. Despite being relatively new, AI applications have already showcased remarkable effectiveness across various industries (Cannella, 2018). Presently, scientists are exploring artificial intelligence from different perspectives, delving into its potential and possibilities (Konnikov et al., 2019). AI presents opportunities that can be harnessed in numerous domains, including human resource management (HRM), where it offers a diverse range of applications (Bhardwaj et al., 2020).
Artificial intelligence plays a crucial role in bridging the gap between education systems and labor markets. With the aid of digital technologies, talented individuals can easily discover suitable job opportunities within the labor market. According to a study by MGI, by the year 2025, online talent platforms have the potential to facilitate 60 million people in finding jobs that align more closely with their skills or preferences. Additionally, these platforms can significantly reduce the costs associated with human resource management, including recruitment, by up to 7% (McKinsey Global Institute, 2017).
Artificial intelligence (AI) is being hailed as a valuable tool for human resource management (HRM). Its implementation in HRM areas like recruitment and selection is rapidly expanding, leading to significant reductions in time and cost associated with these tasks. The potential benefits of AI as a tool to enhance HRM strategy and performance are increasingly acknowledged not only in developed countries but also in developing countries, commonly referred to as the Global South (GS). The Global South comprises low- and middle-income countries across Asia, Africa, Latin America, and the Caribbean (Kshetri, 2021).
Various mechanisms have facilitated the adoption of AI in HRM practices in these economies. Multinational enterprises (MNEs) from the Global North (GN) have followed the pattern of introducing AI-based HRM tools in the Global South (GS), similar to other modern HRM practices discussed in prior studies (e.g., Baddar Al-Husan et al., 2009). An illustrative example of this trend is EY's AI-powered chatbot "Goldie," which had been deployed in 138 countries, including numerous GS economies, by March 2019. Additionally, these economies themselves are actively engaged in developing advanced and innovative AI-based HRM applications. Notable instances of this can be seen in WeChat Recruiting and DIANE (Digital Innovation Assistant for kNowledge Engineering) developed by the Malaysian company Supahands.
AI applications, due to their novelty and resource requirements, often have longer time lags for imitation. Consequently, AI-based HRM tools can offer organizations a means to achieve and maintain a competitive advantage. The potential impact of these tools on HRM practices is substantial. Nevertheless, previous researchers have noted a notable gap between the potential benefits and the actual adoption and implementation of AI in HRM (Tambe et al., 2019). Nonetheless, this gap is narrowing as AI tools continue to evolve rapidly. By harnessing the power of AI, organizations can automate and streamline their HRM processes, resulting in enhanced efficiency, accuracy, and decision-making capabilities.
Therefore, the aim of this study is to investigate the utilization of artificial intelligence (AI) in HRM, using the Ibom E-library as a case study.
1.2 Statement of the Problem
The conventional recruitment process in human resource management (HRM) is often laborious, manual, and susceptible to biases. The process typically involves human recruiters personally reviewing CVs, online profiles, and other sources to identify potential candidates. Recruiters handle all initial contact, provide feedback to rejected applicants, and conduct interviews (O'Donovan, 2019). However, due to human limitations, it is challenging for recruiters to effectively manage all these tasks within the available time, necessitating significant dedication from each individual recruiter.
The identified problem lies in the human limitations, such as biases, preconceptions, and time constraints, which can hinder the effectiveness of the recruitment process (McRobert et al., 2018). This issue can result in organizations missing out on well-suited candidates for a job and incurring financial losses (Baron et al., 2018).
Considering the growing adoption of AI technology in HRM processes, it is crucial to conduct research in this area to gain a deeper understanding of the topic. The Ibom E-library will serve as a case study to explore the implications of AI technology in HRM processes.
1.3 Aim of the Study
The main objective of this study is to explore the application of artificial intelligence (AI) in HRM, using Ibom E-library as a case study.
1.4 Objectives of the Study
The specific objectives are as follows:
- To assess the existing HRM processes and challenges faced by Ibom E-library in their recruitment and employee management.
- To explore different AI techniques and tools that that has been applied by Ibom E-library in the HRM context.
- To examine impacts and limitation of AI adoption in HRM.
1.5 Research Questions
- What are the existing HRM processes and challenges faced by Ibom E-library in their recruitment and employee management?
- What are different AI techniques and tools that that has been applied by Ibom E-library in the HRM context?
- What are the impacts and limitation of AI adoption in HRM processes in Ibom E-library?
1.6 Research Hypothesis
H0: The application of AI has no significant impact on HRM processes in Ibom E-library.
Ha: The application of AI has a significant impact on HRM processes in Ibom E-library.
1.7 Justification of the Study
This study is significant for several reasons. It will contribute to the existing body of knowledge on the application of AI in HRM, specifically in the context of a library organization. It will serve as a reference for other organizations, particularly in the library sector, interested in implementing AI in their HRM practices. It will highlight the potential benefits of AI in improving recruitment efficiency, reducing biases, and enabling data-driven decision-making in HRM. It will contribute to the ongoing discussion on the ethical considerations and challenges associated with AI implementation in HRM.
1.8 Scope of the Study
This study focuses specifically on the application of AI in HRM, using Ibom Elibrary as a case study.
