Impact of Artificial Intelligence for Humanizing Retention Approach

Abstract

In modern digital era where everyone is battling  for the same goal,managing star performers ispivotal to business milestone. The organization is facing acute challenges in maintaining member of workforce,the top management started relying on Artificial Intelligence (AI) to metamorphose human resource management and develop more effective retention plan. AI’s potential to investigate the extensive information warrant HR teams to gain deep understanding into work place dynamics, preferences, and job satisfaction, facilitating the customization of retention process.Predictive analytics in AI has become a radical changein the workforceretention strategies, contributing to the business to visualize the talent in advance of any prospective challenges proliferate. Synchronizing statistical investigation and machine learning, predictive analytics determines the strategy that can predict the possibility of losing out an employee. This dynamic techniquemarks a notable shift from conventional receptive mechanism to cope the attrition. Instead of waiting for employees to resign or disengage, companies can be proactive to create a more supportive and engaging work environment.

This research aims to works ontwo-fold. Predictive analysis is done on both primary and secondary data. Key variables such as job satisfaction, engagement levels, and personal circumstances are analyzed on primary data to generate actionable insights. Sentiment analysis is carried out to analyze the employee feedback on the current work environment.  Machine learning algorithms such as KNN & SVM are used on large employee dataset from Kaggle, andemployees who are likely to leave organization and the reason for their attrition are predicted. Both algorithms are implemented in python and it is found that accuracy of SVM algorithm is better than KNN. The Structural Equation Model was used to test the relationship between Employee Perception and its effect on Job satisfaction and Retention of employees and found that the fit indices fit the model well.From the Multiple Regression it was found that  Job satisfaction was positively associated with employee retention.