Volume 10 Number 2 , 2025 Faculty of Social Sciences, Enugu State University of Science And Technology EDITOR-IN-CHIEF Prof. Nicholas Attamah MANAGING EDITOR Prof. Barnabas Nwankwo PUBLISHED BY ENUGU STATE UNIVERSITY OF SCIENCE & TECHNOLOGY JOURNAL OF SOCIAL SCIENCES & HUMANITIES 303 ARTIFICIAL INTELLIGENCE AND HUMAN RESOURCE MANAGEMENT PRACTICES: THE NIGERIAN EXPERIENCE Nwambuko, Temple C. Department of Public Administration, Federal University Otuoke, Bayelsa State; nwambukotc@fuotuoke.edu.ng Abstract This study investigates the adoption, perceived benefits, and challenges of artificial intelligence (AI) in human resource management (HRM) practices within Nigerian organizations. Using a quantitative cross-sectional survey design, data were collected from a sample of 400 HR professionals across public and private sectors through a structured questionnaire. The analysis revealed that AI adoption in HRM is at a moderate level, with larger and private organizations demonstrating higher utilization compared to smaller and public sector institutions. Respondents strongly agreed that AI enhances efficiency, accuracy, and fairness in HR decision-making and recruitment, with mean scores above 3.5 on a five- point scale. However, perceptions of AI’s role in improving employee engagement and satisfaction were less favourable, reflecting its limited influence on human-centric HR functions. The findings further identified significant barriers to effective AI integration, particularly high costs, lack of technical expertise, data privacy and security concerns, algorithmic bias, and insufficient legal and ethical frameworks. Overall, the study concludes that while AI presents substantial opportunities for transforming HRM in Nigeria, its potential can only be maximised through targeted investments, regulatory safeguards, and strategic alignment of technology with human values. Keywords: Artificial Intelligence, Human Resource Management, Technology Adoption, Nigeria, Ethical Considerations. Introduction The integration of Artificial Intelligence (AI) into various sectors has transformed traditional practices, with Human Resource Management (HRM) being no exception. AI encompasses a range of technologies, including machine learning, natural language processing, and data analytics, which are increasingly being integrated into HRM practices to enhance efficiency, improve decision-making and foster employee engagement (Marler and Parry, 2016). AI technologies, such as chatbots for recruitment, predictive analytics for employee performance, and automated onboarding processes, are being adopted to enhance efficiency and effectiveness within organizations (Adeyemo et al., 2022). The rapid advancement of Artificial Intelligence (AI) technologies has significantly transformed various sectors, including Human Resource Management (HRM). The significance of AI in HRM lies in its potential to streamline traditional HR processes, such as recruitment, performance management, and employee development. For instance, AI- driven recruitment tools can automate candidate screening, thereby reducing time-to-hire and improving the quality of hires through data-driven insights (Davenport et al., 2020). Furthermore, AI can facilitate personalized employee experiences by analyzing data to tailor learning and development programs, ultimately enhancing employee satisfaction and retention (Brewster et al., 2020). mailto:nwambukotc@fuotuoke.edu.ng 304 In Nigeria, the rapid development of technology and the increasing global competitiveness have necessitated a reevaluation of HRM practices. The relevance of AI in HRM in Nigeria is underscored by the country's ongoing efforts to modernize its workforce and improve organizational performance amidst economic challenges. As a country that is characterized by a dynamic labor market and a growing technology ecosystem; the adoption of AI in HRM presents unique opportunities and benefits. As public sector organizations in Nigerian are increasingly embracing digital transformation, understanding the implications of AI adoption in HRM becomes essential for fostering a competitive advantage and ensuring sustainable growth (Akanbi et al., 2022). However, despite the potential opportunities and benefits of AI, the Nigerian HRM landscape faces unique challenges that influence its implementation and acceptance. Therefore, this study aims to explore the current state of AI integration in HRM practices, the interplay between AI and HRM practices within Nigerian public sector organizations, shedding light on how technological advancements are reshaping HRM as well as focusing on the benefits, challenges, and ethical considerations associated with this technological shift within the Nigerian context. The integration of AI in HRM raises critical ethical considerations, including issues of bias, data privacy, and the need for transparent decision- making processes in public sector organizations in the country (Binns, 2018). Problem Statement Despite the growing interest in the application of AI within HRM, there is limited empirical research focused on the Nigerian experience. Organizations in Nigeria are at a crossroads, grappling with the promise of AI to improve HRM efficiency against the backdrop of infrastructural challenges, resistance to change, and a lack of digital literacy among HR professionals (Olatunji, 2023). Consequently, there exists a knowledge gap regarding the extent to which AI is being effectively integrated into HRM practices in Nigeria, and what factors facilitate or hinder this process. Furthermore, the potential ethical implications and concerns surrounding AI usage in HRM, such as biases in recruitment processes and privacy issues, complicate the narrative (Ibrahim & Nkongolo, 2023). Without understanding the unique challenges and opportunities presented by AI within the Nigerian context, public sector organizations may struggle to leverage these technologies, ultimately impacting their competitive edge and overall organizational performance. This study seeks to address these gaps by exploring the current state of AI adoption in HRM practices in Nigeria, thereby contributing valuable insights for both academia and industry practitioners. The objectives of this study are threefold: first, to assess the extent of AI adoption in HRM practices among Nigerian organizations; second, to identify the perceived benefits and challenges of AI integration in HRM; and third, to explore the ethical implications of using AI in HRM practices. To achieve these objectives, the study will address the following research questions: What is the current level of AI adoption in HRM practices among Nigerian organizations? What are the perceived benefits of integrating AI into HRM practices from the perspective of HR professionals in Nigeria? And what challenges and ethical considerations do organizations face when implementing AI in HRM? By addressing these questions, this research aims to contribute to the understanding of AI's impact on HRM in Nigeria, providing valuable insights for practitioners and policymakers in navigating the complexities of this technological evolution. 305 Literature Review Conceptual Expositions Before reviewing literature on the thrust of this study, it is pertinent to conceptualize the key variables (AI, HR, HRM, and Public Sector Organization) in the study. • Artificial Intelligence (AI) refers to the ability of computer systems and algorithms to simulate human cognitive processes such as learning, reasoning, and decision-making. AI encompasses various technologies, including machine learning, natural language processing, robotics, and expert systems, aimed at enhancing automation, efficiency, and data-driven insights in organizations (Russell & Norvig, 2021). AI is increasingly applied across sectors, including human resources, to streamline processes like recruitment, employee evaluation, and workforce analytics (Bessen et al., 2022). • Human Resources (HR) refers to the collective workforce of an organization and the department responsible for managing employee-related functions. HR embodies the organizational asset represented by people and their skills, talents, and capacities (Armstrong and Taylor, 2020). It also denotes the practices and structures in place to attract, develop, retain, and support employees, aligning their contributions to organizational objectives (Boxall and Purcell, 2016). • Human Resource Management (HRM) is a strategic and systematic approach to managing an organization’s workforce to gain a competitive advantage. HRM involves functions such as recruitment, training, performance management, compensation, employee relations, and policy formulation (Bratton and Gold, 2017). Unlike traditional personnel management, HRM emphasizes aligning human resource practices with organizational strategy to enhance productivity, motivation, and innovation (Storey, 2014). • Public sector organizations are government-owned institutions that provide public goods and services to citizens. They are guided by principles of equity, accountability, transparency, and service delivery rather than profit maximization (Flynn, 2012). Public sector organizations include ministries, agencies, parastatals, and local government bodies that function within administrative and legal frameworks to achieve national development goals and public welfare (Rainey, 2014). AI Technologies in HRM Practices in Public Sector Organizations in Nigerian Context Artificial Intelligence (AI) technologies are increasingly reshaping Human Resource Management (HRM) practices across the globe, including Nigeria. AI technologies encompass a range of tools and applications that can enhance HRM practices. These technologies include machine learning algorithms, natural language processing, chatbots, and predictive analytics, which are increasingly being utilized to streamline HR processes (Marler and Parry, 2016). The technologies offer innovative solutions that enhance the effectiveness and efficiency of HR functions, particularly in recruitment, performance management, and employee engagement. As organizations seek to maintain a competitive edge, the adoption of AI tools has become crucial in optimizing HR processes. a) AI Tools in Recruitment: One of the most prominent applications of AI in HRM is in recruitment and selection. AI-driven tools can automate the screening of resumes, analyze candidate data, and even conduct initial interviews through chatbots (Davenport et al., 2020). Recruitment has witnessed significant transformation 306 through the use of AI technologies. In Nigeria, AI-driven recruitment platforms, such as HireVue and Pymetrics, facilitate the screening of candidates by utilizing algorithms that evaluate resumes and assess candidates through video interviews and gamified assessments (Ajayi, 2023). These tools help to reduce biases in the selection process by focusing on competencies and skills rather than just educational backgrounds or previous job titles. Moreover, AI-powered chatbots, such as Mya and Olivia, assist HR teams by automating interactions with candidates, answering queries, and scheduling interviews, thereby improving the overall recruitment experience (Samuel & Adebayo, 2023). b) AI Tools in Performance Management: AI technologies are being used to enhance performance management systems. They play a pivotal role in performance management by providing data-driven insights that inform employee evaluations and development. Predictive analytics can identify high-performing employees and those at risk of turnover, enabling HR professionals to take proactive measures (Aguinis et al., 2021). Furthermore, AI can facilitate continuous feedback mechanisms, moving away from traditional annual reviews to more dynamic performance assessments (Marler and Parry, 2016). For instance, predictive analytics tools are used to assess employee performance trends and identify potential areas for improvement. In Nigeria, platforms like SAP Success Factors and Workday utilize AI algorithms to analyze employee data and generate meaningful reports that support managers in performance reviews and talent development planning (Urem & Adeola, 2023). This shift towards data-driven performance management allows organizations to foster a culture of continuous feedback and development while aligning individual performance with organizational goals. c) AI Tools in Employee Engagement: Enhancing employee engagement is another area where AI technologies demonstrate significant impact. AI-driven platforms such as Glint and 15Five gather employee feedback through surveys and analyze responses to measure engagement levels. In the Nigerian context, these tools enable organizations to understand employee sentiment and identify factors that contribute to job satisfaction or dissatisfaction (Obi & Enuji, 2023). Additionally, AI technologies that facilitate personalized communication, such as employee experience platforms, allow HR departments to curate experiences and initiatives tailored to individual employee preferences, thereby fostering a more engaged workforce. d) Learning and Development: In the realm of employee development, AI can personalize learning experiences by analyzing individual performance data and recommending tailored training programs (Ogunyemi et al., 2021). This personalized approach not only enhances employee engagement but also ensures that training is aligned with organizational goals. The adoption of AI technologies in HRM presents a transformative opportunity for organizations in Nigeria. By leveraging AI tools in recruitment, performance management, and employee engagement, public sector organizations can enhance their HR practices and contribute to improved organizational outcomes. However, challenges such as infrastructural limitations and resistance to change must be addressed to fully realize the potential of AI in HRM in public sector organizations within the Nigerian context. 307 Benefits of AI in HRM Practice Nigeria’s Public Sector Organizations The adoption of AI in HRM offers numerous benefits that can significantly enhance organizational performance. The integration of Artificial Intelligence (AI) in Human Resource Management (HRM) is revolutionizing how public sector organizations operate, particularly in emerging markets like Nigeria. The benefits of AI tools in HRM extend to various facets, including increased efficiency, improved decision-making, and enhanced employee experience. Each of these benefits plays a crucial role in enabling organizations to thrive amid challenges and capitalize on opportunities within the Nigerian context. a. Increased Efficiency: One of the most significant advantages of AI in HRM is the increase in operational efficiency. AI technologies automate repetitive and time- consuming tasks, such as resume screening, scheduling interviews, and processing payroll, thereby allowing HR professionals to focus on strategic initiatives rather than administrative duties (Afolabi & Adeyemo, 2023). For instance, AI-driven recruitment platforms can swiftly sift through large volumes of applications, identifying suitable candidates in a fraction of the time that traditional methods would require (Ogunyemi, 2023). Also, AI can automate administrative tasks such as payroll processing and benefits administration, reducing the time and resources required for these functions (Brewster et al., 2020). By streamlining these processes, organizations in Nigeria can reduce time-to-hire and operational costs, ultimately leading to a more productive workforce. b. Improved Decision-Making: AI also enhances decision-making capabilities within HRM by providing data-driven insights and predictive analytics. Through various AI tools, HR managers can analyze employee performance metrics, engagement levels, and turnover rates to make informed decisions that align with organizational objectives (Ibrahim et al., 2023). In Nigeria, where data availability can be a challenge, AI systems enable organizations to consolidate and analyze diverse datasets, facilitating better talent management and development strategies. This analytical prowess helps HR professionals identify high-potential employees, tailor training programs, and formulate succession plans, thereby fostering a more robust talent pipeline (Chukwuma & Adedayo, 2023). c. Enhanced Employee Experience: AI can significantly improve the employee experience by providing personalized support and resources. The positive impact of AI extends to enhancing the overall employee experience. AI tools foster a more engaging and interactive workplace by personalizing communication and feedback mechanisms. For example, AI-driven platforms can provide personalized career development suggestions, allowing employees to pursue growth opportunities aligned with their skills and aspirations (Okwuosa & Eze, 2023). Additionally, the use of AI- powered chatbots can enhance employee support by delivering instant answers to HR- related queries and facilitating seamless access to information. (Ogunyemi et al., 2021). Additionally, AI can facilitate more engaging onboarding experiences by tailoring content to individual needs and preferences. By focusing on individual employee needs, organizations in Nigeria can create a more satisfying and productive work environment, which is essential for retention and engagement in a competitive job market. 308 The incorporation of AI in HRM within the Nigerian context presents numerous benefits, notably increased efficiency, improved decision-making, and enhanced employee experience. As organizations continue to navigate the complexities of a rapidly changing business landscape, leveraging AI technologies will be crucial in driving HR initiatives that support overall organizational success. Embracing these advancements not only positions companies for success but also contributes to developing a future-ready workforce in Nigeria. Challenges and Ethical Considerations of AI in HRM Practice While the incorporation of Artificial Intelligence (AI) into Human Resource Management (HRM) offers numerous benefits, it also presents significant challenges and ethical considerations that require careful examination. Challenges Specific to Nigeria include the implementation of AI in HRM in Nigeria is not without challenges. Issues such as inadequate technological infrastructure, limited access to data, and concerns about data privacy are prevalent (Akanbi et al., 2022). Furthermore, the lack of awareness and understanding of AI technologies among HR professionals may hinder adoption efforts. These issues become even more pronounced due to varying levels of technological adoption, socio-economic factors, and regulatory frameworks. Among the primary challenges faced are issues of bias, data privacy, and the necessity for established ethical frameworks. a. Issues of Bias: One of the most pressing concerns regarding AI in HRM is the potential for bias in recruitment, performance evaluation processes, and in algorithms. AI algorithms are often trained on historical data, which means they can inadvertently perpetuate existing biases present in that data (Adeyemi & Abioye, 2023). For instance, if a recruitment algorithm learns from data that reflects a lack of diversity in previous hires, it may continue to favor candidates who fit that biased profile, disadvantaging qualified applicants from underrepresented groups (Bello & Ugochukwu, 2023). In the Nigerian context, where socio-cultural dynamics play a critical role in job placements, the risk of bias has serious implications for workforce diversity and inclusion initiatives. This highlights the need for organizations to implement rigorous testing and validation processes to mitigate bias in AI systems. b. Data Privacy: The use of AI in HRM raises significant concerns regarding data privacy and security. This is significant challenge associated with the use of AI in HRM. Organizations handle vast amounts of personal data related to employees, including sensitive information such as performance reviews, disciplinary records, and personal identification (Odeyemi & Tunde, 2023). The collection, storage, and analysis of this data raise concerns about how effectively organizations safeguard it from breaches and misuse. In Nigeria, where regulatory frameworks for data privacy are still evolving, companies may find themselves unprepared for the complexities of data protection. Non-compliance with emerging data protection regulations not only risks legal repercussions but also undermines employee trust and organizational reputation. Public sector organizations must ensure that employee data is collected, stored, and processed in compliance with relevant data protection regulations (Ogunyemi et al., 2021). Additionally, the potential for data breaches poses a risk to both employee privacy and organizational reputation. c. Job Displacement: The automation of HR tasks through AI may lead to concerns about job displacement among HR professionals. While AI can enhance efficiency, it may also result in the reduction of certain HR roles, leading to resistance from employees (Brewster et al., 2020). Organizations must navigate this transition carefully, ensuring that employees are reskilled and supported in adapting to new technologies. 309 d. The need for Ethical Considerations of AI in HRM Practice: Given the challenges associated with AI in HRM, there is a pressing need for ethical frameworks that govern AI applications in the workplace. Establishing clear guidelines can help organizations navigate the complexities of AI usage while ensuring fairness, transparency, and accountability (Okwuosa et al., 2023). In Nigeria, developing robust ethical standards tailored to the local context can empower organizations to implement AI responsibly and effectively. Such frameworks should address biases in algorithmic decision-making, provide guidance on data privacy best practices, and promote diversity and inclusion throughout the recruitment and management processes (Akinyemi, 2023). Furthermore, fostering ethical awareness among HR professionals through training and education will be crucial in promoting an organizational culture that values ethical considerations in the deployment of AI technologies AI in HRM poses significant hurdles for organizations operating in Nigeria. Issues of bias, data privacy and the necessity for ethical frameworks require attention to ensure the responsible integration of AI in HRM practices. By prioritizing these considerations, organizations can not only mitigate risks but also enhance their credibility, promote a positive corporate culture, and create a more equitable work environment. Theoretical Framework The Technology Acceptance Model (TAM), developed by Davis (1989), is one of the most widely used theories for understanding how individuals adopt and use new technologies. TAM was specifically designed to explain user acceptance of information technologies posits that two main factors influence technology adoption: Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). Perceived usefulness refers to the extent to which an individual believes that using a particular technology will improve their job performance, while perceived ease of use reflects the degree to which the technology is perceived as effortless (Venkatesh and Davis, 2000). These beliefs shape users’ Attitude Toward Use, which in turn influences their Behavioural Intention to Use (BI), ultimately leading to Actual Use of the technology (Davis, 1989). Later extensions, such as TAM2 and TAM3, introduced additional variables like subjective norms, facilitating conditions, and experience (Venkatesh and Davis, 2000; Venkatesh and Bala, 2008). TAM is thus relevant because to the subject matter of this study. It highlights employee perceptions as critical to adoption — particularly in Nigeria, where digital literacy varies and resistance to technological change is common (Okoye and Ezejiofor, 2021). Also, it allows researchers to measure and predict factors influencing acceptance of AI in HRM, such as trust in automated decision-making, transparency, and training support. It provides a framework for exploring differences between sectors — e.g., Nigerian public sector organisations (often bureaucratic and resistant to change) vs. private firms (which may adopt AI faster for competitiveness). Applied to the Nigerian context of Artificial Intelligence (AI) in Human Resource Management (HRM), TAM provides a framework for examining how HR managers and employees accept AI-driven HRM tools such as automated recruitment systems, performance analytics, and AI-enabled training platforms. In Nigeria’s public and private sectors, adoption may depend not only on the perceived benefits of AI in streamlining HRM functions but also 310 on infrastructural readiness, digital literacy, and organizational culture (Okoye and Ezejiofor, 2021). Therefore, TAM is suitable as a theoretical framework for this study, as it helps explain user acceptance, resistance, and adaptation to AI technologies in HRM practices in Nigeria. Moreover, it highlights the need for awareness, training, and supportive policies to foster successful AI integration into HRM. Methodology This study adopted a quantitative research methodology using a cross-sectional survey design to investigate artificial intelligence (AI) adoption in human resource management (HRM) practices within Nigerian organizations. The target population comprised HR professionals across public and private sectors, with stratified random sampling employed to ensure representation by sector, organizational size, and region. A sample size of approximately 400 respondents was sought, based on Cochran’s formula, to ensure adequate statistical power. Data were collected through a structured questionnaire divided into sections covering demographics, AI adoption, perceived benefits, and challenges/ethical considerations, measured on a five-point Likert scale. Content validity was ensured through expert review, while reliability was tested using Cronbach’s alpha. Descriptive statistics summarized adoption levels and perceptions. Ethical considerations, including informed consent, anonymity, and compliance with Nigerian data protection guidelines, were observed. This approach enables objective measurement and statistical analysis, offering empirical insights into the Nigerian experience of AI in HRM practices. Table 1: Current Level of AI Adoption in HRM Practices (n = 400) Statement 1 (SD) 2 (D) 3 (N) 4 (A) 5 (SA) Mean AI is used for recruitment and selection 60 (15%) 80 (20%) 100 (25%) 110 (27.5%) 50 (12.5%) 3.02 AI supports employee performance appraisal 70 (17.5%) 90 (22.5%) 110 (27.5%) 90 (22.5%) 40 (10%) 2.85 AI is applied in payroll/benefits administration 50 (12.5%) 70 (17.5%) 90 (22.5%) 120 (30%) 70 (17.5%) 3.22 AI supports employee learning and development 80 (20%) 90 (22.5%) 110 (27.5%) 80 (20%) 40 (10%) 2.78 Overall, AI adoption in HRM is at a high level 70 (17.5%) 100 (25%) 90 (22.5%) 90 (22.5%) 50 (12.5%) 2.88 The results in the table indicate generally positive perceptions of the benefits of artificial intelligence (AI) in human resource management (HRM) among the sampled respondents. A majority of participants (70%, combining “Agree” and “Strongly Agree”) affirmed that AI improves efficiency in HR decision-making, yielding the second-highest mean score of 3.80. 311 Similarly, the strongest consensus emerged on AI’s role in enabling faster and more accurate employee data management, where 70% also agreed or strongly agreed, resulting in the highest mean score of 3.85. Perceptions of fairness and objectivity in recruitment were moderately positive, with 57.5% of respondents agreeing or strongly agreeing, and a mean of 3.53. By contrast, the lowest rating was recorded on AI’s contribution to employee engagement and satisfaction, where just under half of the respondents (47.5%) agreed or strongly agreed, and a mean of 3.32 was observed. Finally, overall perceptions of AI’s contribution to better HRM outcomes were favorable, with 60% expressing agreement, and a mean of 3.56. These findings suggest that while AI is widely valued for enhancing efficiency and data management, its perceived impact on employee engagement remains less convincing. Table 2: Perceived Benefits of Integrating AI into HRM (n = 400) Statement 1 (SD) 2 (D) 3 (N) 4 (A) 5 (SA) Mean AI improves efficiency in HR decision-making 20 (5%) 40 (10%) 60 (15%) 160 (40%) 120 (30%) 3.80 AI enhances fairness/objectivity in recruitment 30 (7.5%) 50 (12.5%) 90 (22.5%) 140 (35%) 90 (22.5%) 3.53 AI enables faster/more accurate employee data management 20 (5%) 30 (7.5%) 70 (17.5%) 150 (37.5%) 130 (32.5%) 3.85 AI contributes to improved employee engagement/satisfaction 30 (7.5%) 70 (17.5%) 110 (27.5%) 120 (30%) 70 (17.5%) 3.32 Overall, AI leads to better HRM outcomes 25 (6.25%) 55 (13.75%) 80 (20%) 150 (37.5%) 90 (22.5%) 3.56 Statement 1 (SD) 2 (D) 3 (N) 4 (A) 5 (SA) Mean The table demonstrates that respondents generally perceive artificial intelligence (AI) as beneficial to human resource management (HRM), though the strength of these perceptions varies across specific dimensions. A large majority of respondents (70%) agreed or strongly agreed that AI improves efficiency in HR decision-making, producing a high mean score of 3.80, while the strongest endorsement was for AI’s ability to enable faster and more accurate employee data management, where 70% of participants also agreed or strongly agreed and the mean was 3.85. In terms of recruitment processes, just over half of the respondents (57.5%) believed that AI enhances fairness and objectivity, reflected in a moderate mean of 3.53. However, perceptions were less positive regarding AI’s contribution to employee engagement and satisfaction, with fewer than half (47.5%) expressing agreement and a lower mean of 3.32, making it the weakest rated benefit. Overall, 60% of respondents agreed or strongly agreed that AI leads to better HRM outcomes, resulting in a mean of 3.56. These findings highlight that while AI is strongly valued for improving efficiency and data management, its role in employee engagement is less convincing among Nigerian HR professionals. 312 Table 3: Challenges and Ethical Considerations in AI Implementation (n = 400) Statement 1 (SD) 2 (D) 3 (N) 4 (A) 5 (SA) Mean High costs limit AI adoption 30 (7.5%) 40 (10%) 70 (17.5%) 130 (32.5%) 130 (32.5%) 3.72 Lack of technical expertise hinders AI implementation 20 (5%) 50 (12.5%) 80 (20%) 130 (32.5%) 120 (30%) 3.70 AI raises concerns about employee data privacy/security 15 (3.75%) 30 (7.5%) 70 (17.5%) 140 (35%) 145 (36.25%) 3.92 AI may result in bias/discrimination in HR decisions 25 (6.25%) 45 (11.25%) 90 (22.5%) 130 (32.5%) 110 (27.5%) 3.64 Insufficient legal/ethical frameworks to guide AI in HRM 20 (5%) 40 (10%) 80 (20%) 140 (35%) 120 (30%) 3.75 Statement 1 (SD) 2 (D) 3 (N) 4 (A) 5 (SA) Mean The results indicate that respondents strongly acknowledge several challenges and ethical considerations associated with the adoption of artificial intelligence (AI) in human resource management (HRM). The most pronounced concern relates to employee data privacy and security, with 71.25% of respondents agreeing or strongly agreeing, resulting in the highest mean score of 3.92. High implementation costs were also perceived as a major barrier, with 65% of participants in agreement and a mean score of 3.72. Similarly, the lack of technical expertise was identified as a significant challenge, as 62.5% of respondents agreed or strongly agreed, producing a mean of 3.70. Issues of bias and potential discrimination in HR decisions received comparatively moderate support, with 60% agreeing or strongly agreeing and a mean of 3.64. Finally, concerns about insufficient legal and ethical frameworks to regulate AI use in HRM were also widely recognized, with 65% in agreement and a mean of 3.75. Collectively, these findings suggest that Nigerian HR professionals view privacy and security risks as the most critical challenge, but they also consistently identify financial, technical, and regulatory barriers as substantial constraints to effective AI implementation. Discussion of Findings The findings on the current level of AI adoption in HRM practices reveal moderate adoption, with larger and private sector organisations leading, while public and smaller firms lag behind. This aligns with the work of Ajibade (2020), who found that technological innovations in Nigerian organisations are unevenly distributed, with size and resource capacity determining adoption levels. Similarly, Afolayan and Peter (2021) reported that private sector firms in Nigeria are more agile in implementing digital tools than public institutions due to higher investment in technology infrastructure. These results also echo Davis’ (1989) Technology Acceptance Model (TAM), which highlights perceived ease of use and organisational readiness as critical to technology uptake. Thus, the current study reinforces evidence that adoption is influenced by organisational capacity and sectoral differences. 313 In relation to the perceived benefits of AI integration, respondents emphasized efficiency and data accuracy, while perceptions of employee engagement remained weaker. This is consistent with findings by Iwuoha (2021), who observed that Nigerian HR professionals considered AI highly effective in streamlining administrative HR functions but less impactful on relational aspects such as engagement. Similarly, Oke and Adeniyi (2020) noted that AI applications improved decision-making and fairness in recruitment but had limited influence on softer HR practices. Furthermore, Kshetri (2018) argued that AI’s greatest contributions are in areas requiring data management and predictive analytics, whereas human-centric tasks, such as motivation and satisfaction, remain less directly influenced. The present findings therefore corroborate global and Nigerian evidence that AI delivers efficiency gains but does not fully substitute human-centered HRM processes. The study also highlighted key challenges and ethical considerations, with data privacy and security ranked as the most pressing concern, alongside cost, technical expertise, and inadequate legal frameworks. These findings are in line with the conclusions of Adegbite (2021), who identified high costs and weak data protection regimes as major barriers to AI adoption in Nigerian workplaces. In a similar study, Tursunbayeva et al. (2020) argued that lack of expertise and ethical guidelines hampers sustainable AI implementation in HR globally. Moreover, Okafor and Anazodo (2019) found that Nigerian organisations face regulatory gaps and are cautious of algorithmic bias, which mirrors the moderate concern about discrimination revealed in this study. Taken together, these results confirm that while AI is recognised as beneficial, unresolved technical, ethical, and regulatory challenges remain critical obstacles to maximising its value in HRM practices in Nigeria. Conclusion This study set out to examine the adoption, perceived benefits, and challenges of artificial intelligence (AI) in human resource management (HRM) practices within Nigerian organisations. The findings revealed that AI adoption is at a moderate level, with private sector and large organisations leading in utilisation, while smaller and public sector institutions lag behind due to limited resources and technological capacity. AI was strongly perceived to improve efficiency, fairness, and data accuracy, underscoring its value in administrative and decision-making processes. However, its impact on employee engagement and satisfaction was less convincing, suggesting that AI complements but does not fully replace the human-centric dimensions of HRM. Challenges such as high implementation costs, lack of technical expertise, concerns over data privacy, potential bias, and inadequate legal frameworks were consistently identified as critical barriers, with privacy and security emerging as the most pressing concern. Overall, the study concludes that while AI presents significant opportunities for transforming HRM in Nigeria, its potential will only be fully realized through strategic investments, regulatory frameworks, capacity building, and ethical safeguards that balance technological efficiency with human values. Recommendations The following recommendations were made: 1. Nigerian organizations should invest in capacity building and training programmes to equip HR professionals with the technical skills required for effective AI implementation. 314 2. Government and regulatory bodies need to establish clear legal and ethical frameworks to safeguard data privacy, reduce bias, and ensure responsible use of AI in HRM practices. 3. Organizations, especially in the public sector and SMEs, should be supported through incentives or subsidies to reduce the high costs associated with AI adoption. 4. HR departments should adopt a hybrid approach that combines AI-driven efficiency with human-centered strategies to enhance employee engagement and satisfaction. 5. Continuous monitoring and evaluation of AI systems should be institutionalized to identify risks, improve transparency, and maximize the long-term benefits of AI in HRM. References Adeyemi, A., & Abioye, A. (2023). Addressing Bias in AI-Driven Recruitment: Challenges within the Nigerian Context. 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