Artificial Intelligence Adoption and Employee Productivity in Technology-Based Organizations

Abstract

Artificial Intelligence has grown to be an integral organizational technology, impacting the way that staff members complete tasks, make choices, course of information and manage everyday activities. As AI-enabled technologies, automation systems, and intelligent decision-support applications become increasingly prevalent, there are opportunities for organizations to enhance employee efficiency and productivity. The impact of AI adoption on employee productivity could, however, vary based on the type of work, employees' skills, and the manner in which AI tools are woven into an organization's operations. The aim of this study was to investigate the link between the use of AI and staff productivity in technology-driven companies. The research design used was the quantitative cross sectional research design, the data collection technique was the structured questionnaire by purposive sampling in which approximately 250 employees were involved. The usage of AI-powered tools, automation systems, and intelligent decision-support applications by employees was used to evaluate the level of adoption of AI, while task completion and work efficiency along with the perception of employee's performance was used to measure employee productivity. To describe the variables' characteristics, descriptive statistics were used, and the association between AI adoption and employee productivity was determined using Pearson correlation. Multiple regression analysis was then used to test if the adoption of AI had a statistically significant impact on employee productivity. The study offers empirical evidence on the role of AI in today's technologically driven work environments and brings in the current debate over the nature of AI as an assistant or as a replacement for human employees.