COVID-19 has a profound global impact on various industry sectors. It has led to significant changes in societal behavior. Social distancing made public spaces hazardous, shifting consumer habits, including purchasing and spending patterns. People have been driven toward online resources and delivery services, causing disruptions and impacting industries. The study investigates and identifies new online food delivery patterns that emerged during COVID-19. We focus on the food delivery industry in a University town, integrating 183 restaurants to understand how e-commerce and consumer behavior with respect to restaurant food delivery changed from pre-COVID to the COVID-19 times. We use AI and machine learning techniques to collect and analyze data collected over three years. Findings suggest that new emerging patterns require adaption to the variability in the types of food that consumers are ordering, ordering times, delivery locations, etc. Such insights provide for resource planning and allocation decisions.