Increasing focus on efficiency and AI Beyond fuels, as industries and societies continue to explore and implement AI, machine learning and automation solutions in a vast range of applications, the aviation sector is leveraging this trend to simultaneously tackle labour, cost and environmental challenges. Some operators, like Alaska Airlines, already leverage AI-driven flight planning platforms, to optimize routes in real time by accounting for weather, airspace constraints and traffic conditions.54 Increasingly, airport operators are testing digital twins (virtual replicas relying on sensor data to monitor conditions and provide real-time simulations) to coordinate operations and reduce energy use.55 Other tried-and-tested high-impact use cases include automated bag loading, AI-powered predictive maintenance and robotic customer assistance.56 This advanced “technology stack” bears the potential to revolutionize the airport ecosystem, by re-configuring entire operations in key areas, such as air traffic management (ATM), surface and ground movement operations, ground support equipment (GSE), passenger experience and aircraft maintenance57 – all dimensions which have been affected by either workforce shortages or safety concerns. Crucially for decarbonization efforts, AI and advanced sensor tools could exponentially improve analytical capabilities to monitor and predict emissions data, thus empowering the aviation industry to accurately reduce and optimize emissions through operational adjustments. With opportunities also come challenges, in the form of paramount safety concerns, infrastructure gaps, re-skilling and loss of employment. Overall, given strong momentum in frontier technologies across industries, 2026 is expected to be a year in which further trials, R&D and regulatory discussions will make this topic more relevant than ever for the aviation sector.Data collection, estimation and usage Conversations on improving contrail impact estimations and traffic management increasingly emphasise leveraging better data, models and partnerships. Tools such as the Travel Impact Model are advancing methodologies to classify flights by contrail warming potential relative to CO2 emissions, improving the granularity and accuracy of climate-relevant estimates used at booking and in planning systems. Google Flights now displays contrail warming risk alongside carbon emissions figures,58 signalling how data transparency can inform carriers and passengers alike. Such innovations are emerging alongside broader digital collaborations: for example, Lufthansa Group announced a partnership with Amadeus in January 2026 to enhance booking and operational efficiency, which could indirectly support sustainability outcomes by improving planning and reducing inefficiencies.59 This development reflects a growing recognition that data integration, from climate impact models to operational systems, is key to optimizing traffic management and reducing aviation’s climate footprint. Regulatory initiatives reinforce this shift towards integrated data use. EASA’s Flight Emissions Label, developed with EUROCONTROL in January 2026, standardizes operational and fuel life-cycle data to estimate flight carbon emissions.60 While it currently excludes contrails and other non-CO2 effects, the required data inputs largely overlap with those needed for upcoming non-CO2 monitoring frameworks, underscoring the value of building data pipelines today with a future total climate impact perspective. Google Flights now displays contrail warming risk alongside carbon emissions figures, signalling how data transparency can inform carriers and passengers alike. Global Aviation Sustainability Outlook 2026 20