TECHNOLOGY SATURATION, DIGITAL DETOX, AND REAL-WORLD SOCIAL BONDS AMONG AI-ORIENTED TECH WORKERS

Authors

  • Anil Bhatt Department of Sociology, Govt. PG College New Tehri, Tehri Garhwal.
  • Swapnil Gaur School of Management, Graphic Era Hill University, Dehradun, Uttarakhand.
  • Neeta Gupta Department of Psychology, D.A.V. (P.G.) College, Dehradun, Uttarakhand.
  • Vandana Gaur Department of Psychology, SDM Govt. PG College Doiwala, Dehradun, Uttarakhand.
  • Shiv Gupta BITS Pilani, Pilani, Rajasthan.

DOI:

https://doi.org/10.70917/ijcisim-2026-4035

Keywords:

Artificial Intelligence, Technological saturation, Digital detox, social bonds, Tech workers, Digital transformation, Mental health awareness, Loneliness, Depression

Abstract

 AI-driven workers of the IT sector face a huge impact on social identity due to the technology saturation that makes them unable to detox digitalisation. This study shows the importance of social life and eliminating high use of digitalisation technologies both in office premises and personal lives. The study has been conducted with the help of an online survey through Google Forms, which has further collected data from 250 participants. Use of IBM SPSS (version 30) in 2024; the software is used to analyse data to understand the relationship between technological saturation, digital detox, and the integration of social bonds. It is being seen that high level of depression from mental breakdown is occurring in the current years in this sector. Key analysis is further obtained from Regression analysis, correlation analysis and descriptive analysis. Thus, this study can be more approachable with the help of secondary qualitative data, which is not being selected. Hypotheses created are further aligned with the analysis and accept it accordingly.

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Published

2026-07-31

How to Cite

Anil Bhatt, Swapnil Gaur, Neeta Gupta, Vandana Gaur, & Shiv Gupta. (2026). TECHNOLOGY SATURATION, DIGITAL DETOX, AND REAL-WORLD SOCIAL BONDS AMONG AI-ORIENTED TECH WORKERS. International Journal of Computer Information Systems and Industrial Management Applications, 18(13s), 90–101. https://doi.org/10.70917/ijcisim-2026-4035

Issue

Section

Original Articles