Transition: Impact on Workforce from Primitive Digital Tools to GEN AI Tools

A Multi-Algorithmic Study on Generative AI Adoption and Workforce Outcomes

Manju Arora*

Abstract

The transformative world from neurons to bits is possible due to Artificial Intelligence which makes life easier. The transition from mundane to quantum work. One of the examples is virtual assistant bots help to manage the workforce and automate the process at your workplace. The tools to improve the task, automation level, employee engagement, remote work, digital literacy affects the different workplace outcomes to predict Role definition, Job satisfaction and Work Agility. The methodology used multi-algorithmic models like Linear Regression model is used to predict the job satisfaction as a continuous variable, XGboost ensemble algorithm is used for calculating workflow agility and clustering is used for Role Definition three different models have been used as per the data type of target variable following algorithms has used. Moreover, Role definition in workplace can be implemented using Clustering, just to compare the performance using accuracy and CH- Index value and the experimental results proves that which is the better approach, K-Fold Cross validation technique will be implemented for better evaluation. The Experimental results will be proven using evaluation parameters like Accuracy, Precision, Recall, F1-Score and Calinski-Harabasz Index. Henceforth results will conclude the transition is effective that will be further validated though the complete study.

Keywords

XGboost, Calinski-Harabasz Index, Multiple Linear Regression, Generative AI, Workforce Transition, Job Satisfaction, Work Agility, Role Definition

Corresponding Author

Manju Arora, Assistant Professor, Department of Information Technology, Jagan Institute of Management Studies, India.

Citation

Arora, M. (2026). Transition: Impact on Workforce from Primitive Digital Tools to GEN AI Tools. J. Cogn. Comput. Ext. Realities, 2(1), 01-07.