ABSTRACT. The purpose of this study is to examine generative artificial intelligence and remote sensing and spatial analytics tools enabling meaningful productivity growth and labor market participation in virtual work environments. In this article, previous research findings were cumulated indicating that immersive haptic experiences can be attained through generative artificial intelligence and cognitive artificial intelligence algorithms, employee engagement analytics, and physiological and behavioral biometrics. The contribution to the literature is by showing that generative artificial intelligence and wearable augmented reality technologies can further virtual employee engagement, talent management, and organizational productivity and effectiveness. Throughout September 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “generative artificial intelligence and productivity software tools” + “adaptive self-organizing and cognitive computing systems,” “wearable augmented reality and algorithmic tracking technologies,” and “immersive workspaces.” As research published in 2023 was inspected, only 177 articles satisfied the eligibility criteria, and 54 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: AXIS, Dedoose, MMAT, and SRDR.
JEL codes: E24; J21; J54; J64

Keywords: immersive workspace; generative artificial intelligence; productivity software tools; adaptive self-organizing and cognitive computing systems; wearable augmented reality and algorithmic tracking technologies

How to cite: Balica, R.-Ș. (2023). “Generative Artificial Intelligence and Productivity Software Tools, Adaptive Self-Organizing and Cognitive Computing Systems, and Wearable Augmented Reality and Algorithmic Tracking Technologies across Immersive Workspaces,” Economics, Management, and Financial Markets 18(2): 77–94. doi: 10.22381/emfm18220234.

Received 14 October 2023 • Received in revised form 24 December 2023
Accepted 25 December 2023 • Available online 30 December 2023