A new report finds AI will help airlines save billions of dollars in cutting delays, operational efficiencies and analysing the mountain of data that is already being generated.
This report and analysis developed by OAG in collaboration with AI provider Microsoft, finds AI will help shape airline operations. Operational and delay rates remain stubbornly high with an estimated USD34 billion cost in the United States in 2022 and every minute costing airlines USD100. Several airlines report up to 30% savings in customer support costs due to AI-driven automation. A series of real world examples of AI in action are highlighted in the OAG report, Can AI and the Right Data Rewrite the Rules of Airline Performance? and include:
. . . Call Centres
Air India’s AI. chatbot autonomously handles 97% of all customer queries without human intervention, notes the report. Built on Microsoft’s AI infrastructure, the system simulates a digital travel agent, using natural voice or text input to guide customers through booking flows in real time. A second AI solution by Air India enables one-click booking, reducing transaction time by up to 90%. By combining traditional user interface design with AI-driven inputs, the system personalises travel suggestions and automates the booking journey.
. . . Efficiency
American Airlines has integrated AI-driven gating technology built on Microsoft Azure. The system analyses real-time flight data, air traffic conditions, and airport logistics to dynamically assign the most optimal gate for arriving aircraft. At Dallas/Fort Worth International Airport, American’s AI-powered gating system has reduced taxi times by over a minute per flight, eliminating up to 10 hours of taxi time daily and saving 3.2 million litres of jet fuel annually.
. . . When in Rome
At Rome Fiumicino Airport (FCO), Assaia’s ApronAI solution uses video analytics and machine learning to forecast aircraft readiness well in advance. By generating real-time timestamps for key turnaround activities, such as passenger deboarding, refueling and catering, the system trains predictive models that estimate departure readiness and pushback times with high accuracy. In airports where ApronAI was deployed in 2023 and 2024, overall ground delays dropped by 6%, and turnaround times improved by 4%, despite increased traffic.
