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The study focuses on how automation influences the workforce productivity with respect to employees' performance and efficiency at The University of Haripur, Pakistan. Quantitative approach is used to analyse questionnaire data through descriptive statistics, using Cronbach’s Alpha for reliability ranging from 0.618 to 0.868, and multiple regression analysis on SPSS. The respondents were 100 employees (53% male and 47% female), the hypotheses were tested considering 7 independent variables: Implementation of Automation, Employee Training and Skill Development, Technology Integration and System Compatibility, Workload Distribution, Flexibility in Work Arrangements, Job Security Perception, Maintenance, and System Downtime, and 1 dependent variable: workforce productivity. Findings of the study reveal that predictors contribute 76% to the dependent variable. The significance value (Sig.) in the ANOVA (shown in Table 4) is 0.025, which indicates that the independent variables have a significant impact on workforce productivity as a whole, indicating that the regression model as a whole is statistically significant. Among all independent variables, only Job Security Perception has a statistically significant impact on Workforce Productivity (shown in table 5). This study recommends that organizations initiate training programs when implementing automation in the workplace. They should focus on the mental stability and reassurance of their employees while maximizing the benefits of automation.

Key Words: Workforce Productivity, Automation, Influence on Employees.