Human resources management in the age of artificial intelligence

In today’s evolving world of work, Artificial Intelligence (AI) has emerged not merely as a technological tool but as a catalyst for rethinking how jobs are structured and performed (Bankins et al., 2024; Parker & Grote, 2022). Across diverse job families and organizational contexts, tools like generative AI (GAI) go beyond mere instruments for data analysis or structuring and can adopt increasingly far-reaching roles through rapid progress in generating new graphic or textual content or algorithmic decision making (Ferràs- Hernández, 2018; Walsh et al. 2019). Central to this symposium is the recognition that this changing nature of work due to digitalization, propelled by AI and related tools, calls for a fresh look at established theories of job design and strategies for human resource management. Traditionally, research has illuminated how fostering characteristics like autonomy, skill and task variety, or adequate demands affect employee motivation, satisfaction, and well-being and thereby further organizational outcomes (Oldham & Fried, 2016; Parker et al., 2017). Yet the introduction of AI – particularly generative AI – adds complexity: Who performs which tasks? How are decisions made, and by whom? Which skills remain uniquely human, and which may be augmented or even entirely adopted by AI? Such questions demand a more nuanced and strategic approach to designing work in the future that balances efficiency and innovation with psychological and ethical considerations. The four presentations in this symposium aim to contribute to theory building on how AI affects work in terms of work design, the interplay of employees and AI use, and work outcomes. In particular, they highlight potential risks or unique challenges when working with AI (e.g., in terms of less enriched work, lowered autonomy levels, threats to job identity or risks due to disclosure of use) and path the way for interventions to achieve benefits of such technologies at work. In detail, the empirical studies in this symposium illuminate these issues at three interconnected levels: 1. Task-Level Insights: Two contributions focus on the more granular task characteristics (e.g., autonomy, skill variety) in modern, AI-enhanced work contexts. They demonstrate how AI use influences the allocation of specific tasks when designing work roles and how the perception of task characteristics changes when AI is used in a decision-making task. 2. Job- and Identity-Level: One paper zooms out from individual tasks to jobs as a whole and explores how AI-driven change might disrupt employees’ job identity. This lens demonstrates how task changes cascade into bigger questions of role definition and identity. 3. Organizational Context: Finally, one presentation adopts the broadest perspective and investigates managerial and organizational factors that might shape employees’ willingness to disclose and ethically integrate AI tools. Taken together, these presentations point toward a future in which AI’s transformative potential hinges on thoughtful coordination across tasks, roles, and organizational systems. By combining established frameworks with new insights drawn from (quantitative and qualitative) surveys and experiments conducted in Germany, Austria, the United States, the United Kingdom, and Australia, these contributions illustrate how AI can enrich, rather than diminish, work and thereby strengthen human-centered organizations. By focusing on variables at different levels, the studies path the way for applications in practice, emphasizing the importance of individual approaches (e.g., training for job design, supporting self-efficacy), or on the organizational level (e.g., aligning HR practices, develop clear and supportive organizational policies and guidelines for the use of AI at work). Investigating the Influence of Work Design Perspective and AI Integration on Enriched Job Design Author: Tanja Bipp; Heidelberg University Author: Thea Ebert; Aalen University Collaborative Intelligence: Integrating Generative AI in Knowledge Work and its Impact on Job Design Author: Sabina Hodzic; University of Graz Author: Simon Grob; University of Graz Author: Bettina Kubicek; University of Graz Job Identity as Starting Point for SHRM in AI-Driven Organizational Change Author: Sophie Berretta; Ruhr University Bochum Author: Annette Kluge; Ruhr University Bochum Silent Adoption: Understanding the Drivers of Non-Disclosure of Generative AI Tools by Employees Author: Fangfang Zhang; Curtin University - Perth

The rapid advancement of artificial intelligence (AI) has significantly influenced human resource management (HRM), presenting both opportunities and challenges for individuals and organizations. This study provides a comprehensive analysis of the integration of AI in HRM, exploring its multifaceted implications on employee perceptions, engagement, and organizational practices. A systematic literature review was conducted, focusing on journal articles published between 2018 and 2024. The review includes studies examining AI’s role in enhancing HR processes, such as recruitment, employee monitoring, performance evaluation, and training, while emphasizing its ethical and legal considerations. Findings reveal that while AI has the potential to revolutionize HRM by streamlining processes and improving decision-making, its application raises concerns regarding employee trust, data privacy, and bias in algorithms. The study highlights diverse perspectives on the relationship between AI and HR, showcasing the dual role of AI as a tool for efficiency and a challenge to human-centric management approaches. A novel contribution of this paper is the development of an AI + HR model framework, specifically designed to assist HR managers in navigating the complexities of AI-driven systems. This framework provides practical insights for leveraging AI in HRM to enhance employee engagement and organizational outcomes. Despite its contributions, the study is limited to a specific timeframe and excludes certain types of literature, such as non-English articles and conference papers. Nevertheless, it offers valuable implications for HR practitioners and researchers by advancing the understanding of AI’s transformative role in HRM.

Artificial Intelligence (AI) is revolutionizing Human Resource (HR) management by enhancing talent acquisition, employee engagement, performance evaluation, and workforce planning. This study explores AI-powered talent management strategies, analysing their effectiveness, advantages, and challenges. By examining AI applications in HR, this paper highlights how organizations leverage AI-driven insights to improve efficiency, reduce biases, and enhance decision-making processes. Furthermore, the study delves into ethical concerns and the future of AI in talent management. Keywords: Artificial Intelligence, Talent Management, Human Resource Management, AI-Driven Recruitment, Employee Engagement, Performance Evaluation, Workforce Planning, Ethical AI

Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy. Ancient civilizations contained tales of intelligent robots, such as Greek and Chinese cultures. AI as a modern phenomenon which took shape in the mid-20th century with the advent of digital computers. The first breakthrough, published in 1950, was Alan Turing's paper, ‘Computing Machinery and Intelligence. AI can make provide detailed solution to users and experts. They can act independently, replacing the need for human intelligence or intervention (a classic example being a self-driving car). Many sectors like finance, healthcare, to human resource management (HRM), rely on AI technologies. AI's integration in HRM has brought about great change in conventional HR practices used to measure efficiency, accuracy, strategic decision-making, etc. AI technologies help to provide solution to automation of repetitive tasks, analysis of sprawling volumes of data and insights facilitating decision-making. Through this research paper we try to understand the AI's effects on HR processes, in terms of recruitment, onboarding, performance appraisal, training and development, employee engagement, workforce planning; understanding the benefits and cons of implementing AI in HRM; ethical considerations and potential biases in AI algorithms relevant to HR practices; analysis of emergent AI trends with respect to HRM. Trends in AI in HR tend towards a most promising future, presenting several innovations. Accordingly, HR professionals will be expected to acquire competency with regards to new roles and responsibilities to avail AI in enhancing strategic planning, ethical oversight, and data-driven decision-making.

The integration of Artificial Intelligence (AI) and digital connectivity can revolutionize material and human resources management in secondary schools. The study focused on human and material resources management in education in Nigeria and its impact on students’ academic performance in secondary schools, in Ebonyi State, Nigeria. Subjects for the study were two hundred (200) students and hundred (100) teachers randomly selected from five secondary schools in Afikpo, Ohozara, and Ezza South Local Government Areas of Ebonyi State. Questionnaire was used to collect relevant data for the study. Pearson Product Moment Correlation was used to analyses the formulated hypotheses. The findings of the study revealed that there was significant positive relationship between human resources management and students’ academic performance (r = 0.814; p < 0.05). Also, significant relationship exists between material resources management and students’ academic performance (r = 0.629; p < 0.05). The implication is that effective material resource management may bring about improvement in student’s academic performance. While it was recommended that effective practice of both human and material resources is to be well implemented for effective performance of students at any level of educational system in Nigeria.

The paradigm of human resource management (HR) has been significantly changed by the introduction of artificial intelligence (AI) after 2024. The HR function no longer focuses on administrative work, but becomes a strategic partner that uses technology to help make decisions, talent management, and improve employee experience. This study aims to analyze the transformation of HR strategies after 2024, identifying the key competencies that HR needs. The research method uses a Systematic Literature Review (SLR) of ten scientific articles published between 2024 and 2026. These articles were obtained via academic databases like Scopus, Google Scholar, ScienceDirect, and Emerald Insight. The results show that AI improves efficiency and analytical capabilities in HR functions, but its success depends on digital skills, ethical technology, and employee mental readiness. To ensure equitable and humane AI adoption, employees must learn a hybrid of skills, such as data analytics, interpersonal skills, ethical leadership, and change management skills

In the context of globalization and rapid technological advancement, the introduction of Artificial Intelligence (AI) has brought new opportunities and challenges to Human Resource Management (HRM). This study constructs an evolutionary game model to explore the strategy choices and evolutionary paths of enterprises and employees in HRM value co-creation with AI involvement. We numerically simulated the dynamic evolution of strategies under different scenarios, revealing the equilibrium characteristics of strategic interactions between enterprises and employees in the AI context. The study finds that, first, the evolutionary game system between enterprises and employees converges to two equilibrium points: {cooperation, active} and {non-cooperation, passive}. Overall, the probability of the former is 2.39 times greater than that of the latter. Second, higher initial probabilities of cooperation and active involvement, along with lower costs for cooperation and active involvement, facilitate the system’s evolution towards the {cooperation, active} equilibrium. Third, enterprises are more sensitive to the benefit distribution ratio than employees. This study provides theoretical support for effectively conducting HRM practices in the AI era through systematic analysis of HRM value co-creation behavior, along with practical policy recommendations.

ABSTRACT: Artificial Intelligence (AI) in talent management is a game-changer to Human Resource Management (HRM) as it alters the way organizations attract, retain, develop and engage employees and is one strategic factor in the 21st century. Talent management powered by AI can further advance recruitment and selection by automating resume screening, enhancing candidate-job fit, as well as minimizing bias, as well as automated on-boarding through AI chatbots and virtual assistants that customize integration. In learning and development, AI facilitates hyper-personalized training, reskilling and up-skilling programs that are aligned to both personal career aspiration and organizational objectives, and in performance management, real-time continuous analytics results in a more objective and productive performance review traditionally kept annual. The positive impact of workforce planning is associated with the ability to predict the skills that will be needed in the future, matching the human resource capital to the business plans. Future of work will focus on human-AI collaboration, where the automation will be human intelligence amplifier, creating agile, resilient and ethical workplaces. In that regard AI powered talent management becomes not only a driver of business performance and the answer to the question of how to create the workforce of the future but also an enabler of building the agile, future-ready workforce. Keywords: Artificial Intelligence, Talent Management, Human Resource Management, Recruitment, Learning and Development.

The integration of Artificial Intelligence (AI) into Human Resources (HR) procedures has heralded the dawn of a new age in the workplace. The purpose of this research study is to shed light on how AI-driven innovations are transforming recruiting, talent management, employee engagement, and the broader HR function. It examines AI's possibilities for decreasing prejudice, increasing efficiency, and optimizing HR decision-making, while also addressing the ethical quandaries and concerns that arise from this fundamental transition. The growing importance of AI and machine learning (ML) in altering HR practices cannot be emphasized. The advent of 'Big Data,' combined with the spread of the Internet of Things (IoT), has created a hospitable environment for breakthrough AI solutions. AI is increasingly being used by businesses to automate HR duties. As a result, AI has the ability to reduce the administrative burden on HR professionals by allowing them to make decisions based on solid data patterns rather than mere guesswork. This conversation digs into AI integration in HR, its benefits, implementation issues, and next steps. Adopting AI and machine learning is critical for precise decision-making and effective staff management. It is critical for HR staff to overcome their fears in order to handle these obstacles. This paper aims to provide a complete knowledge of the emerging HR landscape in the age of AI, presenting insights and ideas to steer enterprises toward a future in which human and artificial intelligence coexist together in the workplace.

Human resources (HR) management addresses those policies, practices, and activities concerned with the management of people in organizations. Although it is typically considered at multiple levels of analysis, it provides an important context for the application of work and organizational psychology. Core research questions address the determinants of HR strategy and practices adopted by organizations and how these are linked to outcomes including in particular organizational performance and employee wellbeing. Much research explores this linkage process including how far HR practices are able to ensure employee abilities, motivation, and opportunities to contribute; the distinctive role of human capital; how employees react to these practices; and the steps management can take to ensure their effective implementation. Most research confirms an association between the adoption of a greater number of what are typically termed “high performance” or “high involvement” HR practices and higher organizational performance and employee wellbeing. However, doubts remain about the causal direction of the association. Continuing research challenges include how best to measure HR practices, understanding more about contextual influences, and incorporating more fully the role of employee attitudes and behavior including employee attributions about the motives of management in their use of HR practices.

Human resource management (HRM) enables making sustainable organisational performance a reality for today›s dynamic business environment. HR practice alignment and organisational strategy have been among the biggest forces driving innovation, employee engagement, and competitive success. This article presents an overview of the history of HRM from administrative work to being an organisational strategy partner and its contribution to organisational performance. Based on extensive literature review and some recent theory such as Resource-Based View (RBV) and Human Capital Theory, in this study an analysis has been presented on how strategic HR practices such as talent management, performance management, employee development, and diversity management have influence on employee›s performance along with organisational performance. The study also addresses the role of leadership, organisational culture, technology such as artificial intelligence, in trying to conceptualise HR effectiveness. For organisational leaders and HR practitioners in best practice and trends in world-class companies, implications of the study are noted. The study reiterates the importance of strategic HRM and alignment of firm strategy in response to changing labour markets and generating long-term value. Research implications are developed to build strategic competencies of HR functions, and suggestions are given for future research..

Artificial intelligence (AI) has the potential to change the world of work radically. Wherever information processing is involved, AI can be integrated into processes with added value. From the perspective of Human Resource (HR) management, this implies three things: first, business models and performance processes in the company will undergo change; second, employee requirements will change; and third, HR processes will change. While the literature describes various AI maturity models, there has been no dedicated consideration of HR management. This article, therefore, aims to identify relevant influencing factors for an AI-orientated approach to HR management and to describe these in more detail using maturity levels in a Human Resources Artificial Intelligence Maturity Model (HR-AIMM). The resulting HR-AIMM consists of eleven dimensions. These include anchoring the AI topic in the corporate and HR strategy, its use in selected HR processes, considering ethical, data-related, and infrastructural principles, and organisational, cultural, and competence-related anchoring. The characteristics of these factors enable the identification of four maturity levels for using AI in HR management: from a curious start to the level of holistic integration. Our framework supports researchers and companies in understanding and evaluating the factors influencing the professional application of AI in HR management.

The article is devoted to highlighting problematic aspects of the implementation of artificial intelligence in the field of jurisprudence, in particular, in certain branches of law. Due to the rapid development of neural network capabilities, artificial intelligence is a tool for quickly completing tasks and processing information in various spheres of society, including in jurisprudence. Therefore, for a comprehensive analysis, it is necessary to identify problem areas for the implementation of such a phenomenon. It is noted that today there is no unified approach to defining the concept of artificial intelligence. The authors provide several definitions of this concept for the most complete understanding of the essence of artificial intelligence. The legislation does not contain a normative legal act dedicated to the issue of the essence and procedure for using artificial intelligence, which gives rise to such dilemmas. Despite the widespread use of artificial intelligence capabilities among citizens, there is a lack of interest, funding and development of educational methods for the effective use of artificial intelligence in professional activities on the part of government authorities. It is also stated that the introduction of artificial intelligence into professional activities requires staffing with specialists who can service the software. The problems of introducing artificial intelligence in the field of legal proceedings are analyzed. The use of artificial intelligence by courts risks undermining the autonomy of courts and the independence of judges. Artificial intelligence is not able to comprehensively evaluate evidence and make decisions based on moral standards. The issues of transparency of courts, guaranteeing fundamental human rights and freedoms, and software reliability remain open. The legal status of artificial intelligence in civil law is considered. Since artificial intelligence is capable of creating a work, questions remain regarding the protection of copyrights using artificial intelligence and legal liability in case of copyright infringement. A debatable and controversial topic is the definition of artificial intelligence as a subject or object in a civil legal relationship. It has been determined that the introduction of artificial intelligence in criminal proceedings can become a factor in increasing cyber attacks on the neural network with the aim of stealing, destroying, and making data public.

Turbulent times and crises force many human resource (HR) managers to adapt human resource practices (HRP) to a rapidly changing reality. The modification of HRP in a very stressful environment poses enormous challenges for HR managers. This study looks at the mechanisms through which HRP was adapted to unexpected changes to attain resilience during worldwide crises. Based on qualitative data collected from 72 Israeli HR managers, the findings reveal that HR managers’ social capital (SC) serves as a mechanism for adapting HRP to attain resilience. HR managers employed personal, intra-organizational, and extra-organizational levels of SC that lead to compatible types of resilience: employee, organizational, and interface resilience. Although personal and intra-organizational SC were used frequently, the HR managers used extra-organizational SC to cope with the upheavals caused by the crises to a lesser extent, and, therefore, less interface resilience was attained through HRP. The findings contribute to the literature by suggesting that HR manager SC serves as a mechanism fueling the adaptation of HRP during crises and leads to resilience. It also extends the resilience literature by suggesting that the adaptation of HRP through HR manager SC influences different types of organizational resilience.

This study aims to explore the integration of artificial intelligence (AI) in human resource (HR) practices, focusing on its role in talent acquisition. By conducting a comprehensive literature review using a qualitative, library research method, this paper examines the current trends, challenges, and opportunities associated with AI adoption in HR, particularly recruitment. The findings highlight that AI has the potential to significantly improve recruitment efficiency, reduce biases, and enhance decision-making processes in HR. However, the study also reveals key ethical concerns related to algorithmic biases and transparency, which can negatively impact fairness in hiring practices. Furthermore, the research emphasizes the importance of upskilling HR professionals to effectively manage AI tools and integrate them into broader organizational strategies. The paper concludes by discussing the need for transparent, ethical AI systems and suggests that further research is necessary to evaluate the long-term effects of AI on HR practices and organizational culture. This study contributes to the ongoing discourse on AI in HR by providing insights into the implications of AI-driven recruitment and offering recommendations for future research in the field.