Wave Energy Conversion (WEC) devices are at a pre-commercial stage of development with feasibility studies sensitive to uncertainties surrounding assumed input costs. This may affect decision-making. This paper analyses the impact these uncertainties may have on investor, developer and policymaker decisions using an Irish case study. Calibrated to data present in the literature, a probabilistic methodology is shown to be an effective means to carry this out. Value at Risk (VaR) and Conditional Value at Risk (CVaR) metrics are used to quantify the certainty of achieving a given cost or return on investment. The certainty of financial return offered by proposed Irish Feed-in Tariff (FiT) policy is analysed. The influence of technological ‘learning’ is also discussed. The model presented identifies those rates of learning required to achieve cost-effective deployment under various cost certainty requirements. The corresponding cost reduction targets for developers are identified. Uncertainty is found to have a greater impact on the investment decision when learning progresses at a slower rate. This paper emphasises the requirement for a premium to account for cost uncertainty when setting FiT rates. By quantifying uncertainty, the presented methodology allows for the required premium to be identified.