The study was an assessment of the impact of First-to-Expire First-Out (FEFO) automation using Artificial Intelligence (AI) on the cost of inventory write-off in listed pharmaceutical companies in Nigeria between 2021 and 2025. The research dealt with the long-term issue of stock leakage as a result of stock obsolescence existing in a fluctuating macroeconomic environment. The study was conducted with the help of two particular objectives: the assessment of the decrease in the volumes of expired inventory and the determination of the influence on the costs of monetary write-offs. The research design adopted the ex-post facto research design where secondary data were used in a census sample of 5 listed firms. The Multiple Regression analysis was employed to analyse the data and triangulate them with Technology Acceptance Model (TAM) and Resource-Based View (RBV). The results showed that there was a strong and statistically significant negative relationship between AI-based FEFO and inventory write-off costs β = -0.612, p < 0.05). The regression model had an R2 value of 0.748, which explained 74.8% of the variation in write-off costs (R2 = 0.748), which means that automation is a major factor contributing to reduction in wastes. The authors found that AI-based FEFO is a powerful strategic financial resource that maintains firm capital. It is suggested, that pharmaceutical boards should make capital investment in AI-integrated ERP systems one of their priorities to balance the profit margins with the loss associated with inventory.