Automating structural analysis processes in engineering is essential to keep pace with rapidly evolving design challenges. Manual simulation setups are not only time-consuming but also prone to errors, which can compromise both safety and efficiency. Automation allows for consistent, repeatable, and scalable analysis methods. This approach is important for optimising complex structures for performance and reliability under varying conditions. This paper explores the integration of Python scripting within ANSYS Workbench as a tool for automating structural analysis. By using Python’s communication with the ANSYS ACT API and the CLR framework, the study demonstrates how engineers can define geometry, apply boundary conditions, and execute multiple simulation scenarios with minimal manual intervention. A detailed case study is presented, where external load data is imported from Excel, systematically applied to update load cases, and analysed to determine maximum equivalent stress values, all in an automated workflow. The approach not only streamlines repetitive processes but also significantly enhances the reliability and efficiency of finite element analyses. This study underscores the potential of scripting to improve simulation practices, important for advanced engineering optimisations.