AI-Driven Automation: Efficiency Booster or Dependency Catalyst
Authors-Mr. Hem Kumar, Dr. Devki Nandan Sharma
Keyword-AI-Driven Automation, Technological Dependency, Efficiency, Regression, Education Sector, Digital Skills.
Artificial Intelligence (AI)–driven automation is rapidly transforming organizational operations, educational systems, and industrial workforces. While automation enhances productivity, accu-racy, and process efficiency, it also raises serious concerns regarding technological dependency, skill erosion, unemployment, and human decision-making displacement. This study explores whether AI acts primarily as an efficiency enhancer or a dependency catalyst. A quantitative survey was conducted among 200 higher education faculty members to examine attitudes toward efficiency gains and dependency risks. Statistical tools including descriptive analysis, Pearson correlation, reliability analysis (Cronbach’s Alpha), and linear regression were applied. The results indicate a moderate positive correlation (r = .46) between efficiency and dependency, implying that as automation increases efficiency, dependency also increases significantly. The study concludes that AI improves performance but poses risks that must be managed through balanced adoption and digital literacy skill development.