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Thematische Bibliographien / AI in Workforce Management / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „AI in Workforce Management“

Autor: Grafiati

Veröffentlicht am 7. Juni 2025

Zuletzt aktualisiert am 2. August 2025

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Sasi, Kiran Parasa. "AI in SAP Fieldglass Contingent Workforce Management." Journal of Scientific and Engineering Research 11, no. 7 (2024): 114–16. https://doi.org/10.5281/zenodo.14191028.

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The integration of Artificial Intelligence (AI) within SAP Fieldglass for managing contingent workforces is revolutionizing how organizations handle their temporary, freelance, and contract labor. By leveraging AI, companies can enhance efficiency, improve decision-making, and optimize resource allocation. This paper explores the impact of AI on contingent workforce management through SAP Fieldglass, highlighting its benefits, challenges, and future potential

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Matonya, Michael M. "Innovation, Artificial Intelligence in Contingent Work-Force Management." International Journal of Engineering and Management Sciences 5, no. 1 (2020): 571–90. http://dx.doi.org/10.21791/ijems.2020.1.47.

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In recent years, the global use of contingent workers is rapidly increasing despite the increasing quantity of artificial intelligence applications in business. The question is "how these companies leverage the use of artificial intelligence to enhance contingent workforce's management?". The ideal goal of this paper is to develop a purely conceptual application of innovation, artificial intelligence (AI) adjacent to contingent workforce management(CWM). The researcher used qualitative information gathered from various authors and observations to reinforce the usage of AI. One of the critical

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Sudheer Devaraju and Tracy Boyd. "AI-augmented workforce scheduling in cloud-enabled environments." World Journal of Advanced Research and Reviews 12, no. 3 (2021): 674–80. https://doi.org/10.30574/wjarr.2021.12.3.0691.

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In a rapidly evolving world of modern enterprises, workforce scheduling is an effective way to achieve operational efficiency and resource optimization. In this research, we investigate the combination of AI driven workforce scheduling solutions with Cloud platforms for the management of dynamic workforces in industries like healthcare, logistics and manufacturing. The integrated systems employ artificial intelligence and cloud computing for scalability and for the power of real time adaptability with optimal resource allocation. In this paper we present a comprehensive study of the key compon

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Nishit, Dhilen Mehta. "Artificial Intelligence Powered Workforce Planning - The Future of Strategic Human Resource Management." International Journal for Scientific Research and Development 12, no. 7 (2025): 68–71. https://doi.org/10.5281/zenodo.14964145.

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Artificial Intelligence (AI) is revolutionizing various industries, Human Resources being one of them. Many organisations have started integrating AI solutions in their workforce strategies and are seeing impressive results. AI can be implemented at any and every stage of workforce lifecycle, beginning from workforce planning to talent management, employee retention, employee satisfaction, general employee management and onboarding/offboarding. AI can be used to build frameworks, strategies and guide autonomous decision making based on inputs from various disparate sources – including in

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Parasa, Sasi Kiran. "AI in SAP Fieldglass Contingent Workforce Management." Journal of Artificial Intelligence & Cloud Computing 3, no. 4 (2024): 1–2. http://dx.doi.org/10.47363/jaicc/2024(3)366.

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Saeed, Maham, Muhammad Saqib Jalil, Fares Mohammed Dahwal, et al. "The Impact of AI on Healthcare Workforce Management: Business Strategies for Talent Optimization and IT Integration." American Journal of Medical Sciences and Pharmaceutical Research 07, no. 03 (2025): 136–56. https://doi.org/10.37547/tajmspr/volume07issue03-15.

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Through Artificial Intelligence (AI), healthcare has brought revolutionary changes to workforce administration by directing talent delegations and reforming operations with IT integration. Healthcare organizations struggle with staff shortages alongside rising operational costs while seeking high-quality patient care which makes AI-driven workforce solutions data-based when addressing these problems. This investigation reveals the ways AI technology brings improved scheduling capabilities along with better talent hiring methods and performance evaluation systems and employee maintenance proced

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Dr. Abraham Rajan and Dr. V. Nagajothi. "AI-Powered Talent Management Strategies in HR: An Analytical Study." International Journal of Scientific Research in Modern Science and Technology 3, no. 12 (2024): 01–03. https://doi.org/10.59828/ijsrmst.v3i12.275.

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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 In

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Shreyas Subhash Sawant. "Neural Workforce Orchestration: How AI Systems Automate Dynamic Resource Management." Journal of Computer Science and Technology Studies 7, no. 5 (2025): 912–21. https://doi.org/10.32996/jcsts.2025.7.5.105.

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AI-powered workforce intelligence revolutionizes organizational management by providing autonomous systems that optimize staffing levels, enhance employee productivity, and maximize operational efficiency. This article explores transformative concepts, including neural network-based data processing, autonomous decision systems, and predictive intervention capabilities. Readers will discover how artificial intelligence enables organizations to autonomously manage workforce scheduling, automatically respond to staffing shortages, and precisely forecast workload fluctuations without human interve

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Adio, Saliu Alani, Zamathula Sikhakhane-Nwokediegwu, Fasasi Lanre Erinjogunola, Rasheed O. Ajirotutu, and Rasheed Kola Olayiwola. "Integrating AI in Public Transport Workforces: A Review of HR Challenges and Opportunities." International Journal of Multidisciplinary Research and Growth Evaluation. 6, no. 2 (2025): 611–24. https://doi.org/10.54660/.ijmrge.2025.6.2.611-624.

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This study provides an in-depth exploration of the integration of Artificial Intelligence (AI) in public transport workforces, identifying the resultant human resources (HR) challenges and opportunities. The main objectives were to understand how AI technologies are being implemented in public transport systems, the impact of these technologies on the workforce, and the role of HR in facilitating a smooth transition. Employing a systematic literature review and content analysis, the study analyzed academic journal articles, industry reports, and governmental publications from 2010 to 2024, foc

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Nishitha Reddy Nalla. "AI-Driven Predictive Analytics for Workforce Planning and Optimization." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 4 (2024): 349–53. https://doi.org/10.32628/cseit2477112.

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Predictive analytics powered by AI is revolutionizing the way organizations plan and optimize their workforce. Through the use of big data, machine learning and AI technologies, organizations can forecast workforce requirements, improve talent management techniques, and drive operational effectiveness. In recent years, the integration of AI-driven predictive analytics in workforce planning and optimization has transformed the way organizations manage talent, enabling them to adapt quickly to changing demands. It also explores the future of AI in human resource management, offering guidance on

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Patel, Amisha. "A STUDY OF THE IMPACT OF AI ON HUMAN RESOURCES MANAGEMENT PRACTICES A STUDY IN SELECT STEEL MANUFACTURING UNITS OF CHHATTISGARH." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–9. https://doi.org/10.55041/isjem03799.

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ABSTRACT: This study explores the impact of Artificial Intelligence (AI) on Human Resource Management (HRM) in selected steel industries of Chhattisgarh. It examines how AI affects core HR functions like recruitment, performance management, training, and employee engagement. Using a mixed-method approach, the research highlights AI’s benefits in improving efficiency and decision-making while addressing challenges such as job displacement and data privacy. The study offers recommendations for ethical and effective AI integration in HRM. It focuses on how AI affects key HR functions like recruit

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Kushwaha, Punam. "THE ROLE OF HUMAN RESOURCES IN IMPLEMENTING ARTIFICIAL INTELLIGENCE IN HOSPITAL MANAGEMENT." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–9. https://doi.org/10.55041/isjem03794.

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ABSTRACT: This research paper explores the strategic role of Human Resource (HR) departments in the adoption of Artificial Intelligence (AI) within hospital management. It highlights how HR facilitates workforce adaptation, ethical AI use, recruitment, training, and performance evaluation in AI-driven healthcare systems. The study examines AI applications like automated scheduling, predictive staffing, and AI-based hiring, while addressing challenges such as employee resistance, ethical issues, and the need for upskilling. Using both qualitative and quantitative methods, the research emphasize

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Ramachandran, Dr P. "HR’s Perspective Towards the Artificial Intelligence in the Selected Sector of Tamil Nadu." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem46617.

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Abstract- Artificial Intelligence (AI) is revolutionizing Human Resource Management (HRM) by improving operational efficiency and decision-making accuracy. AI technologies, which include high-speed computation, vast data sets, and advanced algorithms, enable HR departments to automate routine tasks, optimize workflows, and enhance employee experiences. AI applications in HRM span recruitment, payroll management, talent acquisition, employee engagement, and data-driven decision-making. By automating administrative processes, AI frees HR professionals to focus on strategic activities that add or

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Researcher. "FUTURE FIELD SERVICE BUSINESS OPERATIONS ENHANCEMENT USING AI AND ROBOTS." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 203–13. https://doi.org/10.5281/zenodo.13944129.

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This article explores the transformative impact of artificial intelligence (AI) and robotics on the field service management (FSM) industry. It examines how these technologies are reshaping business processes and operations in field service, focusing on key areas such as predictive maintenance, robotic automation, workforce management, and customer interaction. The paper discusses AI-driven predictive maintenance using IoT sensors and machine learning algorithms, the role of robots in inspections and repairs, AI-enhanced workforce management for optimized scheduling and skill matching, and imp

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Artha, Bhenu, Syakdiah, Nany Noor Kurniyati, and Erna Tri Rusmala Ratnawati. "Artificial Intelligence: A New Paradigm in Human Resource Management." Jurnal Penelitian Pendidikan IPA 10, SpecialIssue (2024): 372–76. http://dx.doi.org/10.29303/jppipa.v10ispecialissue.8609.

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The ability to automate procedures and improve decision-making, artificial intelligence (AI) is quickly transforming a wide range of industries, including human resource management (HRM). The application of AI in different sectors, including HRM, has been predominant and profound. AI has created a disruption by displacing established HRM processes with innovative ones, and its scope includes recruitment and selection, workforce management, and learning and development. AI is enabling machines to make more accurate decisions than humans based on data and behavioral patterns. The integration of

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Sasibhushan, Rao Chanthati. "Project Workforce Management Using Cloud & and Cost Optimization with Artificial Intelligence." Engineering and Technology Journal 10, no. 04 (2025): 4429–35. https://doi.org/10.5281/zenodo.15181837.

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<strong> </strong>In the era of digital transformation, effective workforce management and cost optimization have emerged as critical priorities for organizations worldwide. This study explores the integration of cloud-based technologies and artificial intelligence (AI) to enhance workforce management systems. Traditional methods often fall short in managing remote teams, forecasting staffing needs, and reducing operational overheads. By leveraging cloud platforms, organizations can achieve universal accessibility, real-time monitoring, automated scheduling, and streamlined communication.

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Kumar, Chandan. "From Automation to Ethics: Responsible AI in Human Resource Management across Industries with Insights from the Power Sector." RESEARCH REVIEW International Journal of Multidisciplinary 10, no. 4 (2025): 63–81. https://doi.org/10.31305/rrijm.2025.v10.n4.009.

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The integration of Artificial Intelligence (AI) in Human Resource Management (HRM) is revolutionising workforce management by automating recruitment, performance evaluations, and employee engagement processes. However, AI-driven HRM systems raise critical ethical concerns, particularly regarding bias, privacy, and transparency. This study explores the ethical implications of AI adoption in HRM, with a specific focus on the power sector, where automation plays a crucial role in workforce optimisation. The research employs a quantitative approach, analysing responses from 250 employees across va

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Shuo Xu. "Innovating Artificial Intelligence for Workforce Preparation and Knowledge Development." Journal of Computer Science Research 6, no. 2 (2024): 12–17. http://dx.doi.org/10.30564/jcsr.v6i2.6663.

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Artificial intelligence (AI) transforms workplaces by streamlining operations, automating tasks, and enhancing decision-making. To bridge the knowledge gap in AI best practices, a workshop was created for executives, integrating change management principles. The workshop aimed to help participants understand AI's role, use AI tools for predictive analytics, and develop strategies for leveraging AI in change initiatives. This paper outlines the workshop's impact on building confidence, knowledge, and positive attitudes towards AI in the workplace.

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Researcher. "UNVEILING THE FUTURE WORKFORCE DYNAMICS: LEVERAGING TECHNOLOGY FOR HR STRATEGIES, EXPLORING THE PITFALLS." International Journal of Management (IJM) 15, no. 6 (2024): 14–21. https://doi.org/10.5281/zenodo.14095265.

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This study investigates the influence of Artificial Intelligence (AI) on human resource management (HR) strategies in the contemporary digital era. It examines the transformative effects of AI, data analytics, and automation on talent management processes including recruitment, employee development, and workforce planning. This study elucidates the advantages of these technologies, such as enhanced efficiency and decision-making capabilities, while concurrently addressing challenges pertaining to privacy concerns, algorithmic bias, and potential workforce displacement. This research underscore

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Khair, Mohammad Afghanul, Nusrat Shaheen, Mohammed Misbahul Khair, and Shalu Jain. "HCM AI Agents and Data-Driven Decision Making." International Journal of Research in Modern Engineering & Emerging Technology 13, no. 3 (2025): 36–54. https://doi.org/10.63345/ijrmeet.org.v13.i3.3.

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In the modern enterprise landscape, Human Capital Management (HCM) is undergoing a paradigm shift, leveraging artificial intelligence (AI) agents and data-driven decision-making. AI-powered HCM solutions optimize talent acquisition, workforce planning, and employee engagement by harnessing machine learning, natural language processing, and predictive analytics. These intelligent agents enhance efficiency by automating repetitive HR tasks, such as recruitment screening, performance evaluations, and employee sentiment analysis. Furthermore, data-driven insights empower HR leaders to make strateg

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Selvamohana K. "From HR Analytics to AI-Driven HRM: Enhancing Workforce Productivity and Engagement." Journal of Information Systems Engineering and Management 10, no. 21s (2025): 578–85. https://doi.org/10.52783/jisem.v10i21s.3395.

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The rapid evolution of Human Resource Management (HRM) has been significantly influenced by advancements in Artificial Intelligence (AI) and data analytics. Traditional HR practices, which relied on manual decision-making and intuition, have been transformed by HR analytics, enabling data-driven workforce management. The integration of AI into HRM has further revolutionized employee engagement, talent acquisition, performance management, and workforce productivity. This paper explores the transition from HR analytics to AI-driven HRM, emphasizing its role in enhancing organizational efficiency

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Devarapalli, Shivareddy, Abhishek Jain, and Monu Sharma. "Reinventing HR with AI and Workday: Integration Strategies for the Digital Enterprise." Global Journal of Human Resource Management 13, no. 2 (2025): 38–46. https://doi.org/10.37745/gjhrm.2013/vol13n33846.

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The digital transformation of human resources (HR) is accelerating with the convergence of Artificial Intelligence (AI) and advanced Human Capital Management (HCM) platforms like Workday. This paper explores strategic approaches to integrating AI capabilities within Workday to reinvent HR functions, enhance workforce intelligence, and drive enterprise agility. Key focus areas include AI-driven talent acquisition, predictive analytics for workforce planning, automated performance management, and intelligent employee experience platforms. The study presents integration models, architectural fram

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Jagtap, Samiksha, Amey Kadam, and Om Kadam. "Inventrove with Real-Time Face Recognition Using AI." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem43628.

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Efficient workforce management is crucial in in- dustrial environments where precise monitoring of employee attendance directly impacts productivity and operational ef- ficiency. This paper presents the design and implementation of an advanced attendance management system tailored for industrial applications, which integrates biometric authentication and facial recognition technologies. The system leverages real- time data processing capabilities to ensure accurate and auto- mated tracking of employee attendance, eliminating traditional manual errors and enhancing security. The proposed soluti

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Joshi, Satyadhar. "The Transformative Role of Agentic GenAI in Shaping Workforce Development and Education in the US." IRE Journals 8, no. 8 (2025): 199–206. https://doi.org/10.5281/zenodo.14853885.

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<em>Abstract</em>- This literature review explores the role of Generative AI in workforce development, education, and business management, with a focus on AI-driven reskilling, higher education transformations, labor market shifts, and business intelligence advancements. By analyzing 25 recent studies, this paper categorizes key themes and presents a structured evaluation of AI’s current impact and future potential. The review aims to identify measurable findings, research gaps, and areas for further investigation, offering a foundation for understanding how AI is reshaping economic and

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Regier, Paul, and Lisa Salamonson Grace. "The Role of AI in Recruitment and Employee Development." Journal of Humanities and Social Sciences (JHASS) 5, no. 3 (2023): 130–36. https://doi.org/10.36079/lamintang.jhass-0503.472.

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Integrating Artificial Intelligence (AI) in talent management is reshaping the workforce landscape, especially for global companies in the United States. This study investigates how AI is transforming talent management processes, including recruitment, employee development, and performance management while exploring its implications for organizational efficiency, decision-making, and employee engagement. The research aims to understand the benefits and challenges of adopting AI tools in these processes, particularly in the context of U.S.-based multinational companies. A mixed-methods approach

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Nishitha Reddy Nalla. "Predictive HR Analytics: Forecasting Workforce Needs with AI and Big Data." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 5 (2024): 1085–88. https://doi.org/10.32628/cseit2494114.

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The rapid advancements in artificial intelligence (AI) and big data analytics are transforming human resource (HR) management. Predictive HR analytics enables organizations to anticipate workforce needs, optimize talent management, and enhance employee engagement. This paper explores the role of AI and big data in forecasting workforce trends, discusses various analytical models used in HR, and highlights real-world applications. Furthermore, it examines challenges, ethical considerations, and future research directions in predictive HR analytics.

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Kasali, Kemisola Modinat. "Optimizing Workforce Efficiency in the United States (U.S.) Federal Sector: The Role of Predictive Analytics and AI in Human Resource (HR) Decision-Making." International Journal of Research and Scientific Innovation XII, no. III (2025): 1062–68. https://doi.org/10.51244/ijrsi.2025.12030082.

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The U.S. federal government is undergoing a critical workforce transformation, driven by initiatives under the Department of Government Efficiency (DOGE) to optimize resource allocation and reduce bureaucratic redundancies. This shift poses significant challenges in maintaining service quality amid workforce reductions but offers opportunities to enhance operational effectiveness and public service delivery through technological innovation. Predictive analytics and artificial intelligence (AI) offer strategic, data-driven solutions to enhance human resource (HR) decision-making that enables fe

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Oyekunle, David, and David Boohene. "DIGITAL TRANSFORMATION POTENTIAL: THE ROLE OF ARTIFICIAL INTELLIGENCE IN BUSINESS." International Journal of Professional Business Review 9, no. 3 (2024): e04499. http://dx.doi.org/10.26668/businessreview/2024.v9i3.4499.

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Purpose: The integration of Artificial Intelligence (AI) into business operations has become a pivotal driver of innovation and efficiency. This research paper explores the multifaceted landscape of AI implementation in businesses, examining the benefits of AI implementation. Theoretical Framework: The methodology adopted for this research comprises Semi-structured interviews with six key stakeholders’ executives, AI project managers, and digital transformation staff. Six additional globally businesses were chosen for case studies based on AI adoption maturity and digital transformation perfor

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Temjanovski, Riste, Afrim Loku, and Zlatko Bezovski. "Transforming Human Resource Management in Healthcare: The Role of Artificial Intelligence and Industry 5.0." Journal of Economics 10, no. 1 (2025): 54–71. https://doi.org/10.46763/joe2510154t.

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The healthcare sector is undergoing a transformative shift driven by the integration of Artificial Intelligence (AI) and the principles of Industry 5.0. This paper explores how AI is revolutionizing Human Resource Management (HRM) in healthcare, enhancing operational efficiency, optimizing recruitment and talent acquisition, and fostering employee engagement. Industry 5.0 introduces a human-centric approach that emphasizes collaboration between humans and advanced technologies, prioritizing employee well being and creating a more resilient workforce. This study also highlights the experiences

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Wenting, Li, Wan Mohd Hirwani Wan Hussain, Jia Xinlin, Meng Na, and Syed Shah Alam. "Analyzing the Impact on Talent Acquisition and Performance Management." Journal of Organizational and End User Computing 36, no. 1 (2024): 1–30. http://dx.doi.org/10.4018/joeuc.342603.

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The aim of this research is to explore the mediating and moderating effects of various HR functions and regulatory environments on the relationship between AI integration and data-driven decision making in HRM. The study was conducted in a corporate sector in Malaysia, focusing on businesses actively integrating AI into their HRM functions. A total of 376 individuals successfully submitted the questionnaire, representing an 83.5% response rate. The direct and indirect effects of Workforce Planning (WP), Learning and Development (LD), Employee Engagement and Retention (EER), Performance Managem

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Amaleshwari, U., and R. Shanmugapriya. "Better Catchment of Workforce for Elevating Workplace Performance Integrating AI – A Systematic Literature Review." Shanlax International Journal of Management 11, S1-Mar (2024): 215–24. http://dx.doi.org/10.34293/management.v11is1-mar.8100.

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Combined team of skilled and unskilled employees refers Workforce in any organisation, being the key factor behind anenterprise significant growth integrated with Artificial Intelligence (AI) and Generative AI at various industrial sectors. Theiroverall development rolls on possible with the workforce existing with agility and ability to conduct difficult workplace tasks in a hassle-free, dutiful manner. Mitigating challenges are present within most organizations that even the leaders and legendary stakeholders face in establishing proper managerial strategic methods in successful maintenance

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Suryanarayan, Anusha. "The New Era of Talent Management: Embracing the Future of Work." NHRD Network Journal 18, no. 1 (2025): 45–47. https://doi.org/10.1177/26314541251325697.

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Imagine a world where your workday starts with a personalised wellness plan and ends with real-time feedback that keeps you motivated and engaged. This article envisions such a workplace in the year 2030, highlighting key trends and strategies that will shape talent management. It discusses the importance of hyper-personalisation of employee experiences, leveraging AI for customisations and the expansion of flexible benefits for multigenerational workforces. The article also emphasises the role of predictive analytics and workforce planning in making informed talent decisions. Additionally, it

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Barua, Tonmoy, Jafrina Jabin, and Sunanda Barua. "ECONOMIC TRANSFORMATION OF DATA ANALYTICS THROUGH AI: EMERGING OPPORTUNITIES AND CHALLENGES IN THE WORKFORCE." ACADEMIC JOURNAL ON SCIENCE, TECHNOLOGY, ENGINEERING & MATHEMATICS EDUCATION 4, no. 3 (2024): 32–43. http://dx.doi.org/10.69593/ajsteme.v4i03.87.

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The integration of Artificial Intelligence (AI) in data analytics is revolutionizing various industries, driving significant economic transformation, and reshaping the workforce. This study explores the multifaceted impact of AI-driven data analytics, highlighting both the promising opportunities and formidable challenges it presents. Key findings demonstrate that AI significantly enhances data processing capabilities, leading to improved decision-making and operational efficiencies. Furthermore, the emergence of new job roles such as data scientists, AI specialists, and machine learning engin

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Researcher. "IMPACT OF ARTIFICIAL INTELLIGENCE ON HUMAN RESOURCES MANAGEMENT." International Journal of Computer Engineering and Technology (IJCET) 15, no. 4 (2024): 595–609. https://doi.org/10.5281/zenodo.13348360.

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This article explores the transformative impact of Artificial Intelligence (AI) on Human Resources (HR) management. It examines how AI is revolutionizing various aspects of HR, including recruitment and hiring, employee onboarding, performance management, employee engagement, administrative tasks, workforce planning, and compliance and risk management. The article discusses the benefits of AI in enhancing efficiency, providing data-driven insights, and enabling more strategic decision-making in HR processes. It also addresses the challenges and ethical considerations associated with AI impleme

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Maharaj, Ashika, and Grace Oluwafunmilayo Obalade. "Artificial intelligence innovations in talent recruitment, retention, diversity mapping within South Africa: A meta narrative analysis." Journal of Infrastructure, Policy and Development 9, no. 2 (2025): 10352. https://doi.org/10.24294/jipd10352.

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This paper uses existing studies to explore how Artificial Intelligence (AI) advancements enhance recruitment, retention, and the effective management of a diverse workforce in South Africa. The extensive literature review revealed key themes used to contextualize the study. This study uses a meta-narrative approach to literature to review, critique and express what the literature says about the role of AI in talent recruitment, retention and diversity mapping within South Africa. An unobtrusive research technique, documentary analysis, is used to analyze literature. The findings reveal that S

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Gupta, Dr Neelam, and Achintya Kumar Gupta. "Business Management with Artificial Intelligence." Journal Global Value XVI, SI (2025): 28–34. https://doi.org/10.31995/jgv.2025.v16isi7.005.

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Artificial Intelligence (AI) is transforming business management by enhancing decision-making, optimizing operational efficiency, and driving strategic innovation. This research examines the integration of AI in various business management functions, including marketing, finance, human resource management, and supply chain operations. AI-powered tools, such as predictive analytics, machine learning algorithms, and intelligent automation, enable businesses to streamline processes, improve customer experiences, and gain competitive advantages. Additionally, AI facilitates data-driven decision-ma

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Researcher. "TRANSFORMING CONTACT CENTER WFM THROUGH ARTIFICIAL INTELLIGENCE: IMPLEMENTATION AND IMPACT." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 2228–38. https://doi.org/10.5281/zenodo.14388162.

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Artificial Intelligence (AI) is fundamentally transforming workforce management (WFM) in contact centers, offering unprecedented capabilities in forecasting, scheduling, and performance optimization. This technical article examines how AI-driven WFM solutions leverage machine learning algorithms and predictive analytics to enhance operational efficiency and service delivery. Through an analysis of key components, including intelligent scheduling systems, real-time performance monitoring, and automated coaching mechanisms, we demonstrate how AI integration can reduce operational costs while imp

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Zainuddin Hamidi, Dendi, Ridwan Hakiki, and Hendrik Pandiangan. "AI and Human Collaboration: The Future of HR in the Fourth Industrial Revolution." Escalate : Economics and Business Journal 2, no. 01 (2024): 17–25. http://dx.doi.org/10.61536/escalate.v2i01.49.

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This study investigates the interplay of Adoption of Advanced HR Technologies, Workforce Management Effectiveness, Employee Engagement and Productivity, and Employee Performance within PT Danareksa (Persero), a prominent state-owned enterprise in Indonesia's financial services sector. Using a quantitative approach and Structural Equation Modeling (SEM) with Smart PLS, data from 80 employees were analyzed to explore the direct and indirect relationships among these variables. The findings reveal significant direct effects of Adoption of Advanced HR Technologies and Workforce Management Effectiv

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FERDINAND, SOMIDO TAN DUOJIAO. "AI in Human Resource Management: Balancing Innovation and Human-Centric Strategies." International Journal of Research 12, no. 4 (2025): 702–8. https://doi.org/10.5281/zenodo.15346034.

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The integration of Human Resource Management (HRM) and Artificial Intelligence (AI) is poised to reshape the modern workplace by streamlining processes and enhancing decision-making. The adoption of AI in HRM presents unique opportunities to improve organizational efficiency, automate routine tasks, and optimize strategic workforce management. This study explores the role of AI in HRM and examines how organizations can effectively implement AI technologies while maintaining a balance between automation and human-centric approaches.

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K, ABINESH. "A Study on Artificial Intelligence in Human Resource - Challenges." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem46047.

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ABSTRACT Artificial Intelligence (AI) is transforming Human Resource (HR) management by enhancing efficiency, decision-making, and strategic planning. This study investigates the integration of AI in HR functions such as recruitment, employee engagement, performance evaluation, and workforce analytics, while focusing on the challenges that accompany this technological shift. Key issues explored include data privacy concerns, ethical implications, bias in AI algorithms, resistance to change, and the need for new skill sets among HR professionals. The research emphasizes the importance of balanc

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Ali, Asif, and Dr Nosheen Rafi. "Enhancing Human Resource Management Through Advanced Decision-Making Strategies: Harnessing The Power Of Artificial Intelligence For Strategic, Data-Driven, And Judicious Choices." Migration Letters 21, S8 (2024): 881–89. http://dx.doi.org/10.59670/ml.v21is8.9488.

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This research paper explores the topic of improving HRM procedures by incorporating sophisticated decision-making techniques, with an emphasis on artificial intelligence (AI). AI technologies have completely changed many facets of organizational operations, and human resource management is no exception. HR practitioners may optimize workforce management procedures and promote company performance by utilizing AI to make strategic, data-driven, and wise decisions. The various ways that AI can support HRM tasks, such as hiring and selection, performance management, training and development, and e

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Manoj, Parasa. "AI-Powered Workforce Forecasting in SAP Time Management: Predictive Models for Staffing Needs, Absenteeism, and Peak Demand Planning." European Journal of Advances in Engineering and Technology 12, no. 04 (2025): 17–19. https://doi.org/10.5281/zenodo.15387284.

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This research explores the application of Artificial Intelligence (AI) in SAP Time Management to enhance the accuracy and responsiveness of workforce demand forecasting. It solves forecasting staff requirements, absenteeism trends, and demand spikes using predictive models of historical attendance trends, company calendars, and external data. With machine learning algorithms implemented through SAP Analytics Cloud and SAP Business Technology Platform, the research demonstrates how companies can transition from reactive to proactive workforce planning. The research process involves data ingesti

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Madhuri, A., and B. R. Kumar. "HR Analytics and Decision-Making: A Data-Driven Approach to Employee Performance Management." Journal of Neonatal Surgery 14, no. 7S (2025): 409–23. https://doi.org/10.52783/jns.v14.2425.

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In the era of digital transformation, HR analytics and data-driven decision-making (DDDM) have emerged as strategic tools for enhancing workforce management and organizational performance. This study examines the impact of HR analytics—spanning talent acquisition, employee performance, training and development, and engagement—on DDDM and its subsequent influence on employee productivity, retention, and overall organizational success. Furthermore, the study explores the moderating role of technology adoption in strengthening the impact of DDDM on key workforce outcomes. The study employs struct

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Ivchyk, V. "TOWARDS ETHICAL AND SUSTAINABLE DEVELOPMENT IN BUSINESS MANAGEMENT WITH AI." Grail of Science, no. 40 (June 18, 2024): 76–82. http://dx.doi.org/10.36074/grail-of-science.07.06.2024.008.

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This article considers into the ethical considerations surrounding the integration of artificial intelligence (AI) in business management. As AI becomes more prevalent in decision-making and operations, businesses encounter numerous ethical challenges. These include concerns about algorithmic bias, transparency, workforce implications, and data privacy. The ethical implications of AI in business are complex and far-reaching. This thorough analysis examines real-world examples, ethical frameworks, and best practices to help businesses responsibly navigate these challenges. By proactively addres

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Taneja, Deepti, Surbhi Khanna, Mukul Kumar Shrivastava, Vidya Dayinee Sharan, Vandana Madaan, and Shweta Singh. "Revolution of financial services: analysing the impact of ai on banking sector." Salud, Ciencia y Tecnología - Serie de Conferencias 4 (March 29, 2025): 1389. https://doi.org/10.56294/sctconf20251389.

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Purpose – This study explores the transformative impact of artificial intelligence (AI) on banking, insurance, and investment firms within the financial services sector. It aims to examine the challenges faced by businesses and establish clear research objectives.Design/methodology/approach – The study adopts a descriptive research methodology, leveraging both primary and secondary data sources. Standardised questionnaires and expert interviews provide in-depth insights into AI adoption within the Indian banking sector.Findings – The study identifies key applications of AI in financial service

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Yudi Kurniawan Budi Susilo, Nurulhuda Noordin, and Fariza Hanis Abdul Razak. "Bibliometric Analysis of Artificial Intelligence Integration in HRIS for Strategic Upskilling." Journal of Mathematics and Computing Science 11, no. 1 (2025): 59–74. https://doi.org/10.24191/jmcs.v11i1.8096.

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The integration of artificial intelligence (AI) into Human Resource Information Systems (HRIS) has revolutionised workforce management, enabling strategic upskilling and aligning employee capabilities with organisational goals. This study employs a bibliometric analysis to explore the academic landscape of AI integration in HRIS, focusing on its transformative potential in talent acquisition, performance management, and personalised learning. Drawing from a dataset of 535 publications from 2014 to 2024, the analysis highlights key trends, including the growing emphasis on AI-driven training an

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Dr Rakesh Kumar Pathak and Dr Prakash Upadhyay. "Recruitment Process using Federated AI: An Unbiased Approach." International Research Journal on Advanced Engineering and Management (IRJAEM) 3, no. 03 (2025): 579–84. https://doi.org/10.47392/irjaem.2025.0093.

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Artificial Intelligence is changing almost all aspect of one’s life, directly or indirectly. Those who have nothing to do with computer science or its applications, cannot say that they are not at all affected by AI. Employment is something that affects everyone’s life. AI is transforming the recruitment process significantly. For recruiters it is a big challenge to hire people who are most suitable for the positions they are being hired. Those being hired not just have to have the required skill set but also should be fit in the organization in all respect. They should be academically, techni

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Upadhyay, Divya. "Exploring and addressing AI challenges in HRM: Insights and evidence from the UAE workforce." Human Resources Management and Services 7, no. 1 (2025): 4132. https://doi.org/10.18282/hrms4132.

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Purpose: This article explores the adoption of Artificial Intelligence (AI) in Human Resource Management (HRM) in the UAE, focusing on the critical challenges of fairness, bias, and privacy in recruitment processes. The study aims to understand how AI is transforming HR practices in the UAE, highlighting the issues of bias and privacy while examining real-world applications of AI in recruitment, employee engagement, talent management, and learning and development. Methodology: Through case study methodology, detailed insights are gathered from these companies to understand real-world applicati

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Kessi, Andi Makkulawu Panyiwi, Ayyub Daeng Pananrang, Feronica Fungky Muchsidin, Muhammad Rizal, and Ramlah Ramlah. "The Role of Leadership in Effective and Efficient Human Resource Management Decision Making." Paradoks : Jurnal Ilmu Ekonomi 8, no. 2 (2025): 509–24. https://doi.org/10.57178/paradoks.v8i2.1153.

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This study examines the role of leadership in effective and efficient human resource management (HRM) decision-making. It analyzes leadership styles, including transformational, adaptive, ethical, and AI-driven leadership models; it explores how leadership strategies influence key HRM functions such as recruitment, talent retention, workforce planning, and performance management. Furthermore, the research addresses the integration of data-driven decision-making and AI technologies in optimizing HRM strategies while maintaining ethical and human-centered leadership principles. This study adopts

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Manisha Anil Vhora, Vidya Bhandwalkar, and Prashant Mangesh Rege. "AI-driven HR analytics: Enhancing decision-making in workforce planning." Scientific Temper 15, no. 04 (2024): 3299–308. https://doi.org/10.58414/scientifictemper.2024.15.4.39.

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Conventional workforce planning methods have been revolutionized by the incorporation of artificial intelligence (AI) into human resource (HR) analytics. The effect of AI-powered HR analytics on organizational decision-making is examined in this paper. Organizations may use predictive analytics, data mining, and machine learning to make educated judgments about talent management, employee performance, and retention tactics. The research employs a quantitative technique, gathering information from 150 individuals via survey questionnaires to assess how well AI-pushed HR analytics may also enhan

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