Ai as Employee Performance Evaluation: An Innovative Approach in Human Resource Development

The integration of Artificial Intelligence (AI) in Human Resource Management (HRM) has garnered significant attention due to its potential to revolutionize decision-making, streamline operations, enhance employee engagement, and improve overall organizational efficiency. This study aims to explore the benefits of incorporating AI technologies into HRM processes and to provide insights into the impact of intelligent automation on workplace outcomes. A systematic review methodology was employed, drawing data from prominent databases such as Web of Science, Elsevier, and Google Scholar. Initially identifying 150 records, a rigorous screening process resulted in the exclusion of 94 records based on predefined eligibility criteria. Subsequently, 24 reports were assessed for eligibility, revealing key themes related to the integration of AI in HRM. The findings highlight the importance of leveraging AI to enhance performance management, planning, decision-making agility, and employee development. The study underscores the need for a cohesive framework that positions HRM as a key player in bridging the gap between AI implementation and workplace outcomes. Further research is recommended to address gaps in understanding the interconnected nature of AI implementation and its implications for organizational success.

Artificial Intelligence (AI), a fundamental aspect of the Fourth Industrial Revolution, has become a pivotal concern across various industries, including business management. It is increasingly applied in fields such as marketing, human resource management (HRM), and manufacturing. Within HRM, AI and machine learning technologies are utilized to enhance employee experience, provide personalized training, and analyze HR data for informed decision-making. This integration of technology into HRM, traditionally a people-focused domain, represents a significant shift. AI technology adoption in HRM has surged in prominent settings. For instance, IBM has leveraged AI solutions like Blue Matching, CogniPay, and Watson Career Coach to streamline HR operations. Blue Matching predicts mobile tasks based on employee profiles, while CogniPay aids managers in decision-making by evaluating performance. Watson Career Coach offers personalized career guidance. However, notable cases like Amazon’s AI Recruitment Program have highlighted concerns regarding biases. Artificial intelligence is reshaping various aspects of our lives, including recruitment practices. As more businesses harness AI for candidate selection and evaluation, there’s a growing interest among HR managers in adopting AI solutions. However, this technological advancement also brings challenges, such as the displacement of existing job roles and the need for additional professionals to manage the evolving landscape. Understanding the potential benefits and challenges of AI in recruitment is essential for informed decision-making in HRM.

This study experimentally investigates initial trust formation in the organizational context of an artificial intelligence (AI) system in human resource management (HRM). Drawing on social exchange theory and leader‐member exchange theory, we identify factors that contribute to initial trust in AI through cognitive and affective processing from the perspective of employees in the Chinese context. An online survey (N = 426) was conducted with a 2 (explanation of AI: without vs with) × 2 (trust in leaders: low vs high) design. Our findings demonstrate that initial trust plays a crucial role in AI adoption, and a trustworthy leader increases employees' AI trust and intention to adopt. Providing AI's benefits and risks moderates initial trust and the pathway to adoption. Moreover, familiarity with AI's application in HRM and organizational collectivism is also beneficial. Our findings suggest that organizations should prioritize cultivating initial trust in AI with employee‐oriented strategies, including trusted leadership and supportive training resources.

This study aimed to explore the factors influencing undergraduate nursing students' use of artificial intelligence (AI) tools in their studies, examining how this usage shapes their learning experiences and perceptions of traditional pedagogical approaches. The integration of AI into healthcare is rapidly transforming clinical practice, which in turn necessitates a corresponding shift in nursing education. While AI's potential benefits and challenges in education are widely discussed, limited research has focused on how nursing students specifically use these tools in their nursing studies and how this impacts their learning processes. A qualitative study employing exploratory and descriptive designs. Participants were recruited from an undergraduate nursing program at a tertiary university. Thematic analysis was used to analyze interview data. Key findings revealed that nursing students use AI for personalized learning, bridging the theory-practice gap and managing time constraints. International students particularly found AI valuable for cultural adaptation and language support. A significant finding was the "open secret" of AI use, with students actively using tools despite institutional discouragement, highlighting a disconnect between student needs and institutional practices. Ethical concerns, such as bias, data privacy and accountability, were also prominent. This study provides novel insights into the student-driven demand for AI integration in nursing education. It highlights the need for institutional responsiveness, transparency and the development of ethical AI frameworks. By acknowledging student agency and fostering collaborative dialogue, nursing education can leverage AI's benefits effectively while upholding the profession's core values: compassion, empathy and human-centered care.

PurposeThe purpose of this paper is to argue that human resource development (HRD) needs to embrace and include futures and foresight learning (FFL) as a new addition to its field of theorising and practice. The question to consider is: How can FFL become a new feature of HRD? A key part of the authors’ argument is that the inclusion of FFL will enable HRD to add to the success of any organisation and make a vital contribution to the management of people at work.Design/methodology/approachThis paper firstly considers some of the debates surrounding the meaning of HRD. The authors suggest that instability of the time serves to disturb any comforts that have been created in HRD and that there is a need to consider how there might be different futures for what we still call HRD in research, practice and praxis. This paper then considers how FFL might become one possibility for expanding the existing boundaries of HRD. The authors characterise futures and foresight as a learning process, which provides new but complementary features to what is already considered as HRD. This paper will show how FFL can lead to organisation's success and the way this can be achieved.FindingsThere is a wide variety of meanings of the term HRD; however, HRD is still cast as a “weakened profession” which has to play a subservient role to others in the workplace. Over the last 15 years, the expansion of the meaning of HRD has been seen as evidence of its evolving and emerging nature and development based on a co-creation with other disciplines. This creates a space for FFL, defined as an ongoing learning process to find predictable, probable, possible and/or a variety of long-term futures. FFL embraces three key processes of scanning, futuring and reconfiguring, all of which contain a high potential for participants and others to learn as they proceed, providing outcomes at each stage. FFL has been shown to enhance organisation performance and success and HRD interventions can play a key part in implementation. This represents a significant opportunity for the HRD profession to move from weakness towards strength.Research limitations/implicationsFor HRD researchers, while FFL is not yet on its radar, the authors would argue that the uncertainties of the future require that more attention be given to what might lie ahead. Indeed, HRD researchers need to ask the question: What is the future of HRD research? In addition, if the authors’ call for FFL to be included in the practice of HRD, such practice will itself provide new pathways for HRD research. Further research questions might include: To what extent is FFL practiced in organisations and what role do HRD practitioners play in delivery? How does FFL impact on organisation behaviour and outcomes? What new products and services emerge from FFL? What new skills are required to deliver FFL? Can FFL enhance the status of HRD practitioners in the work place and its role in decision-making? and How can the HRD profession develop as a hybrid profession with respect to machine learning (ML)/artificial intelligence (AI)?Practical implicationsFFL produces outcomes that have importance for strategy, HRD practitioner can learn to facilitate FFL by action learning and in leadership development programmes. FFL offers a significant opportunity to enhance the importance of HRD in organisations and beyond. FFL offers those involved in HRD a significant opportunity to transfer ideas into practice that have an impact on organisation sustainability. HRD can play a significant role in the design and delivery of ML and AI projects.Originality/valueThis paper concludes with a call for embracing FFL as a challenging but important addition to how we talk about learning at work. The authors argue that FFL offers a significant opportunity to enhance the importance of HRD in organisations and beyond. At its centre, FFL involves learning by people, groups, organisations and machines and this has to be of concern to HRD.

Orientation: Organisations are undergoing digital transformation and incorporating artificial intelligence (AI) into business processes and functions. The use of AI technologies, instead of people to perform specific low-level repetitive tasks has become common practice.Research purpose: The research aimed to investigate the impact of AI technologies on the South African workforce, specifically from the perspective of senior human resource (HR) managers.Motivation for the study: The adoption and implementation of AI, robotic process automation (RPA) and large language models, such as ChatGPT in a business, change the way personnel perform specific tasks, interact and participate in business processes.Research approach/design and method: The study used a qualitative research design and a deductive approach. A survey with open-ended questions was conducted among senior HR managers working for leading manufacturing organisations and institutions in South Africa. Content analysis was used to analyse the responses.Main findings: Human resource managers emphasised the importance of AI and RPA in remaining globally competitive and streamlining business and HR processes, highlighting the need to empower the workforce, identify ideal employee traits for AI and RPA integration and effectively manage these technologies within organisations.Practical/managerial implications: The senior HR managers offered advice on how to manage the use of AI and RPA technologies in an organisation.Contribution/value-add: The study highlights senior HR managers’ perceptions of the use and impact of AI and RPA in organisations in South Africa

Human Resource and Research Capacity Development as a Prerequisite of Successful Inclusion of the Republic of Croatia into the European Union

In the context of rapid digital transformation, artificial intelligence (AI) technologies implementation is becoming crucial for e-commerce competitiveness. According to Eurostat, in 2024, 13.48% of EU enterprises use AI technologies, showing growth from 8.0% in 2023. Given Ukraine's European integration aspirations, there is a need to study and adapt EU experience in implementing AI in e-commerce. The research aim is to analyze transformation processes in e-commerce systems under AI technologies influence, study EU experience, and identify development directions for Ukraine. Methodology is based on a systematic approach combining: analysis of relationships between e-commerce components, statistical analysis of quantitative data, comparative analysis of EU and Ukraine indicators, and economic modeling to assess AI implementation effects. Analysis revealed differentiation in AI implementation across the EU by enterprise size (from 11.21% for small to 41.17% for large companies) and countries (leaders - Denmark (27.58%), Sweden (25.09%), Belgium (24.71%)). In Ukraine, AI implementation is 6.9%. Priority areas identified: text processing (26.9%), speech generation (21.2%), and speech recognition (18.7%). Recommendations for phased AI implementation were developed considering enterprise size and industry specifics, with three implementation horizons and differentiated approach. The recommendations can be used for e-commerce enterprises' digital transformation strategies and state support programs. The proposed adaptation mechanisms optimize AI implementation and enhance Ukrainian enterprises' competitiveness. Further research will focus on industry-specific AI implementation strategies and their economic efficiency evaluation in European integration context.

Due to the continued growth of the global services sector, it is essential that service firms have a greater understanding of the implementation of human resource development (HRD) in different cultures and how HRD relates to service quality. The purpose of this article is to develop a theoretical model that stresses the importance of HRD alignment with national and organizational culture in increasing perceptions of service quality. In this article, we present a model that integrates the role of national culture, organizational culture, and HRD into a conceptual framework and develops several propositions. This article suggests that the overall effectiveness in service quality will likely increase when HRD interventions are aligned with the national culture and organizational culture. HRD managers in service firms should understand the role of national culture and organizational culture when implementing HRD. Managers who fail to consider national values and their relationship with organizational culture will be less successful at implementing HRD.

People are among the most valuable assets, as they are intellectual capital, and they are an important factor in determining enterprises’ efficiency and competitiveness. Since modern challenges require high adaptability and professionalism from employees, developing human resources in agricultural enterprises is gaining increasing importance. The modern agricultural sector is undergoing transformations that include integrating digital technologies, process automation, artificial intelligence, and precision farming technologies, which significantly change approaches to management and require new competencies from employees. The article studies modern approaches, trends, and directions for human resources development in agricultural enterprises. It has been proven that today, the development of human resources in the agricultural sector is a synthesis of the latest technologies, sustainable development, and human capital. This is not just training employees in new technologies or agronomic techniques but a comprehensive improvement in the quality of human resources, from developing technical and soft skills to strengthening environmental and social responsibility. This is the path to the efficiency and sustainable development of the agricultural sector, which will continue to meet not only economic requirements but also environmental and social challenges. It has been determined that the development of soft skills is becoming a key factor in the success of agricultural enterprises. Soft skills allow them to adapt to changing conditions, improve teamwork, and help implement innovative solutions quickly. High-quality soft skills in employees help agricultural enterprises remain competitive in the market and be more effective. It has been established that the development of human resources in agricultural enterprises is based on innovation, orientation towards sustainable development, and digitalization. Success depends on the ability of such enterprises to adapt to new market conditions, implement modern technologies, and attract young professionals with the necessary skills. Keywords: agricultural enterprises, human resources, communication, competencies, digitalization, soft skills.

This study investigates how artificial intelligence (AI) impacts academic writing, examining how it might improve language proficiency while addressing moral dilemmas. It explores AI's benefits and possible downsides via bibliometric analysis, emphasizing its impact on various academic fields and the necessity of a methodical, moral integration into language training. This review analyzes research on AI in academic writing using bibliometric methods. Publications from Scopus (2014-2024) were examined with the keywords “AI in academic writing." Data were processed through CSV, Excel, RIS, VOS viewer, and Map chart. The study identifies trends, top authors, institutions, and key research clusters in this domain. Artificial intelligence technologies, including ChatGPT and Grammarly, are acknowledged for their contributions to the improvement of writing fluency, grammatical precision, and reader engagement; however, apprehensions surrounding academic integrity and the ethical utilization of artificial intelligence continue to exist, underscoring the necessity for a judicious and ethical integration within academic contexts. This study explores the increasing significance of artificial intelligence (AI) in scholarly writing. AI applications such as ChatGPT and Jenni AI enhance writing proficiency but provoke ethical dilemmas, including issues of plagiarism and dependency. It is essential to reconcile the advantages of AI with ethical considerations.

In the Industry 4.0 arena, human resource management and development are important tasks for public and private sectors to prepare adequate skilled human resources for organizations' daily work, company operations, and agencies' management and administration activities. Long-term investment on an organization's employees to upgrade their knowledge, abilities, and skills will in turn increase their productivity and the organization's performance. Employees with new technological knowledge and technical skills will be able to contribute to their organization and hence to the nation to boost its economy. This chapter discusses charismatic and transformational leadership that can enhance human resource development and practices and proposes some recommendations to overcome the challenges faced in human resource development.

The development of human resources in the public sector is inseparable from the application of “social man” hypothesis theory. At this stage, there are still many problems in the development, management, and use of human resources in the public sector. Especially in the development and use of human resources in the public sector, there are still outstanding problems such as incomplete development and inappropriate use. Apply the “social man” hypothesis theory, scientifically develop human resources in the public sector, achieve “personal and post-fit” in the introduction and selection of talents, achieve “all-round development” in the cultivation of talents, and in the management education of talents do a good job of “equal attention to grace and power”.

This article delves into the transformative effects of Artificial Intelligence (AI) on precision agriculture, also known as AgriTech or AgTech. The convergence of AI and farming practices reshapes the industry by leveraging machine learning, data analytics, and automation to optimize resource allocation and decision-making. Precision agriculture maximizes crop yields while minimizing waste through real-time data from AI technologies such as remote sensing, satellite imagery, and IoT sensors. AI-driven insights enable precise recommendations for irrigation, fertilization, and pest control, enhancing productivity and reducing environmental impact. Moreover, AI enhances crop health assessment, accelerates genetic research, and fosters climate-resilient crops. The article explores AI's potential in predictive analytics, genetic editing, global food security, and sustainable practices. Automation in agriculture tasks via AI-driven robotics and machinery elevates productivity. While AI offers positive environmental impact through resource optimization and energy efficiency, concerns about energy consumption and hardware management warrant attention. A balanced approach to AI's development, embracing energy-efficient algorithms and renewable energy integration, ensures its positive contribution to sustainable practices. The article concludes by discussing potential research directions and the complex interplay of AI's benefits and environmental concerns.

Technology used to perform tasks requiring intelligence is referred to as artificial intelligence. It is a technological device intended to perform tasks that a human could. Artificial intelligence has resulted in significant changes to today’s organisations. Since human resource management is the area where the majority of employees work, it is important to examine not just one aspect of the company but all of its activities and how they impact it separately. This study proposes a conceptional framework of artificial intelligence (AI) technology application for human resource management (HRM). This review highlights the role of AI in human resource management. Most of the organization has been using artificial intelligence or digital technologies in HR like chatbot, machines learning, and robot process automation in human resource management which support in recruitment, screening, onboarding, and interviewing etc. Therefore, AI implementation should be considered a good expectation opportunity, because AI improves lives, AI builds a better future if properly understood and applied to the right way.