The banking sector has been undergoing a broader digital revolution in recent years, including robotic process automation. Hence, this study examines the impact of the robotic processes on enterprise performance, emphasizing Access Bank of Nigeria as the study's focus. Specifically, the study examined (i) the effect of speed of service on employees' satisfaction. (ii) the influence of the accuracy of data processing on employees' work quality. (iii) the influence of scalability on employees' commitment. A descriptive research approach was adopted, and the staff of Access Bank of Nigeria served as the population. The sample size of 131, calculated through Taro Yamane's (1967) method, was used with simple random sampling to collect primary data from the respondents. A partial least squares structural equation model (PLS-SEM) was adopted to examine the causal relationship through SmartPLS 3.0. The results showed that all robotic process factors substantially predict enterprise performance; employees' satisfaction, employees' work quality, and employees' commitment all have R-squared values larger than 20%, which means that the model of robotic process (speed of service, accuracy of data processing, and scalability) accounts for a substantial amount of the volatility in these dependent variables. The study concluded that the robotic process significantly contributes to high performance in the banking industry in an emerging economy. Bank managers in emerging economies should promote scalability that may help ensure consistency in the outcome during the robotic process. Keywords: Robotic Process; Enterprise Performance; Scalability; Accuracy of Data; Speed of Service