How does AI-driven automation affect job security and morale among permanent employees versus contract workers

Abstract

Artificial Intelligence (AI)-driven automation is rapidly transforming workplaces by increasing efficiency, reducing operational costs, and changing the nature of work across industries. While AI offers significant opportunities for productivity and innovation, it also raises concerns regarding employment stability and employee well-being. This study examines the impact of AI-driven automation on job security and employee morale by comparing the experiences of permanent employees and contract workers. The research explores whether differences in employment status influence employees’ perceptions of job insecurity, career prospects, workplace motivation, and organizational commitment in an increasingly automated environment. Using a comparative research approach, the study proposes to collect quantitative data through structured questionnaires from employees working in organizations that have adopted AI-based technologies. Statistical techniques such as descriptive statistics, independent sample t-tests, correlation, and regression analysis can be employed to examine differences between the two groups and identify the factors influencing job security and morale. The study considers variables including perceived job security, trust in AI, organizational support, opportunities for reskilling, and overall job satisfaction. The findings are expected to demonstrate that contract workers experience greater job insecurity and lower morale than permanent employees following the implementation of AI-driven automation. However, the study also anticipates that effective organizational communication, employee training, and reskilling initiatives can mitigate these negative effects for both groups. The research contributes to the growing body of literature on AI and human resource management by providing empirical evidence on the differential impact of automation across employment types. The study offers practical recommendations for policymakers, human resource professionals, and organizational leaders to develop inclusive AI adoption strategies that protect employee well-being while maximizing the benefits of technological advancement.