,
Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology , Chennai , India
,
Erode Arts and Science College , Erode , India
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Bharathiyar University , Erode , India
,
Gobi Arts & Science College , Gobichettipalayam , India
,
Termez University of Economics and Service , Termez , Uzbekistan
,
Assam Down Town University , Guwahati , India
Nandha Engineering College , Erode , India
The fast development of digital technologies has transformed the organization and work relations, and the process of the digitalization of Human Resource Management (HRM) has become significant in optimizing the performance of the organization. In this paper, I am going to examine how Artificial Intelligence (AI), flexible work environments, and strategic HRM influence organizational productivity, agility, and resilience in a technologically driven work environment. The aim is to investigate the role of the AI-based HR systems and data-driven policies as a means to organize the management of the workforce in the framework of remote and hybrid work models. The study utilizes a conceptual and analytical research approach, which summarizes recent works about AI-based HR systems, cloud-based teamwork software, and strategic HRM models. A conceptual framework, which is named MTV, is suggested to demonstrate the interrelationships between AI-enriched HR practices, digital workplaces, and organizational performance. Based on the results, AI-based recruitment, performance measurement, and decision-support systems have a tremendous positive influence on operational efficiency, employee productivity, and strategic alignment. Moreover, flexible work technologies, when combined with strategic HR policies, will improve the engagement of the employees and the flexibility of the organization. The paper has made a conclusion that the successful digitalization of HRM assumes the system-level implementation of AI technologies, secure digital spaces, and data-oriented strategic planning. The ethical application of AI, the problem of data privacy, and the ability to interoperate on the systems are also key challenges. The findings provide great conclusions to the researcher and practitioner, and it is important to note that the future areas of research on AI-enabled HR ecosystems, particularly in organizations that are transforming with technological growth movements, are of interest.
This is an open access article distributed under the Creative Commons Attribution Non-Commercial License (CC BY-NC) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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