ABSTRACT. This article reviews and advances existing literature concerning automation-based algorithmic decision-making processes, artificial intelligence work structuring function reconfiguration, and big data-driven employee training in productive and collaborative workplaces. Throughout January 2024, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “algorithmic organizational decision-making processes” + “real-time artificial intelligence workforce and employee big data analytics,” “holographic display and interconnected monitoring devices,” and “talent and performance management tools.” As research published in 2022 and 2023 was inspected, only 178 articles satisfied the eligibility criteria, and 36 mainly empirical sources were selected. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: BIBOT, CASP, MMAT, Nested Knowledge, PICO Portal, and SluRp.
JEL codes: E24; J21; J54; J64

Keywords: artificial intelligence; workforce; big data analytics; interconnected monitoring device; talent and performance management; algorithmic organizational decision-making process

How to cite: Popescu, G. H., Zabojnik, S., Durana, P., Poliakova, A., and Tudosă, P. (2024). “Real-Time Artificial Intelligence Workforce and Employee Big Data Analytics, Holographic Display and Interconnected Monitoring Devices, and Talent and Performance Management Tools for Algorithmic Organizational Decision-Making Processes,” Psychosociological Issues in Human Resource Management 12(1): 112–128. doi: 10.22381/pihrm12120246.

Received 27 January 2024 • Received in revised form 22 May 2024
Accepted 24 May 2024 • Available online 29 May 2024