Scope creep presents a persistent problem in Agile software development, frequently undermining test automation efficiency and the overall effectiveness of quality assurance processes. Despite widespread recognition of scope creep’s disruptive effects, existing research primarily offers qualitative assessments or generic risk mitigation strategies, lacking a robust, quantitative framework to measure its specific impact on test automation workflows. Addressing this gap, the present study introduces the Scope Creep Impact Metric (SCIM), a novel risk-based quantification model that integrates key factors such as scope change complexity, test execution stability, and defect detection trends. The research employs a mixed methodology, leveraging empirical data from Agile project environments including test automation logs, defect reports, and practitioner surveys to statistically validate SCIM and benchmark its performance against traditional quality assurance metrics. Key findings highlight the inadequacy of conventional risk models, such as McCabe’s Cyclomatic Complexity and Defect Density Analysis, which fail to account for the dynamic, evolving nature of scope creep in Agile sprints. By offering a structured, predictive approach, SCIM enables Agile teams to proactively assess and mitigate the cascading risks of uncontrolled requirement changes. This study identifies a significant gap in current practice: the absence of data-driven, actionable metrics for quantifying and managing scope creep’s real-time effects on Agile test automation. The proposed SCIM framework aims to bridge this gap, enhancing both academic research and industry best practices for quality assurance risk management in Agile development.