Abstract: A system and method for dynamically determining a price adjustment based on current external market conditions at the time of request for a price from an end user. The system leverages various Al models. The external market conditions can include: historical sales data, booking data for flights not flown, scheduling data, cluster data to identify similar flights, holidays, seasonality data, competitive pricing and schedule data, weather data, external event data, consumer loyalty data. Data is provided initially to train the models, typically for the previous one to three years, and then subsequently at regular intervals to achieve as near-real time processing as is needed.