Harnessing Artificial Intelligence for Enhanced Performance Management in Organizations: A Case Study of Safaricom, Kenya

Abstract

Performance management plays a pivotal role in organizational success by ensuring that employees contribute effectively towards achieving strategic goals. In recent years, the incorporation of artificial intelligence (AI) into performance management has emerged as a transformative trend, providing organizations with new tools to enhance efficiency, objectivity, and overall effectiveness in evaluating and optimizing employee performance. The specific objectives of the study were: assessing the impact of AI integration on performance management, evaluating employee satisfaction within the context of AI-enhanced performance management, and examining the effectiveness of AI in addressing performance gaps at Safaricom. The study adopted descriptive research designs. The study targeted 3250 employees, in (6) departments at Safaricom, Kenya. The study used stratified random sampling design to select (4) departments where 165 employees were selected. Data was collected using a semi-structured questionnaire and key informant interview guide. Quantitative data was analyzed using SPSS version 22.0 software. Inferential statistics in the form of multiple regression and descriptive statistics was used to analyze the data. Descriptive statistics (percentages, mean, and frequencies) were presented in tables and figures. Qualitative data was analyzed using content analysis which involved identifying, coding, and categorizing the content of the data into patterns/themes. The most common narratives were then quoted. The analysis revealed a significant positive association between AI Integration and Performance Management (Coeff/beta = 0.325, P-Value = 0.045), indicating that each unit increase in AI Integration corresponds to a 0.325 increase in Performance Management. However, Employee Satisfaction within AI lacks statistical significance (Coeff/beta = 0.315, P-Value= 0.075). Effectiveness of AI in addressing performance gaps shows no significance (Coeff/beta = 0.305, P-Value = 0.065). The study concludes that The Impact of AI Integration on enhanced Performance at Safaricom reflects overwhelmingly positive perceptions, particularly in optimizing resource allocation and operational efficiency. Diverse opinions and challenges highlight the need for targeted improvement strategies to leverage AI's potential for enhancing performance management.