Manufacturers are increasingly seeking technologies that ensure high product quality while improving operational efficiency. Automatic Optical Inspection (AOI) systems, enhanced by recent advances in Computer Vision (CV), offer consistent defect detection through Non-Destructive Inspection (NDI). However, high initial investment costs and limited awareness of their economic benefits still hinder their widespread industrial adoption. This paper presents a comprehensive cost model to support decision-makers in evaluating the financial feasibility of replacing human-based visual inspection with AOI systems. The model includes a detailed breakdown of both the investment costs and the potential annual savings, considering inspection-related operational costs, internal and external repair costs, unnecessary rework, and even the impact of future sales losses caused by undetected defects. A reverse-calculation method is also proposed to estimate the threshold of revenue loss that would justify the investment under a desired payback period. The proposed model provides a practical and flexible tool to support informed investment decisions. An application to a real-world case study in the automotive industry demonstrates the applicability of the model and confirms the potential of AOI to deliver a short payback period. By quantifying key economic drivers, this work contributes to making AOI adoption more transparent and accessible for manufacturing companies.