Impact of Artificial Intelligence Adoption on Employee Productivity and Job Satisfaction in the IT Sector

Abstract

The swift integration of Artificial Intelligence (AI) tools, especially generative AI, has revolutionized workflows within the Information Technology (IT) industry. This research explores AI's dual effects on employee productivity and job satisfaction by employing a mixed-methods approach that merges quantitative survey data from 850 IT professionals in key tech regions with qualitative interviews. The results indicate notable productivity improvements, with AI users experiencing a 25-35% average increase in task completion rates, particularly in areas such as coding, debugging, data analysis, and documentation. Nonetheless, the impact on job satisfaction is complex: moderate AI usage is linked to greater satisfaction due to fewer routine tasks and increased creativity, whereas extensive AI adoption may cause technostress, underutilization of skills, and reduced autonomy, leading to an inverted U-shaped relationship.

Regression analysis reveals that elements such as training, managerial backing, and an organization's exploratory orientation positively influence these results. The productivity advantages are most significant for workers with less experience, whereas job satisfaction depends on well-defined integration plans. The research proposes that a strategic approach to AI implementation—focusing on collaboration between humans and AI, skill enhancement, and ethical management—can optimize benefits while reducing risks. For IT managers, the implications involve creating customized adoption frameworks to maintain workforce engagement during technological changes. This study adds to the expanding body of literature on AI's impact in the workplace by offering empirical evidence specific to sectors and practical recommendations.