Transportation companies are facing increased pressure from investors, regulators and customers to drive decarbonization efforts. Recent regulations designed to accelerate decarbonization will likely impact not only transportation companies but also businesses that engage transportation and freight logistics services in their upstream or downstream supply chains. This demonstrates the imperative for transport and freight logistics service providers to decarbonize: they need to meet their own targets and regulatory requirements for direct emissions (scopes 1 and 2) as well as helping their customers across all sectors to meet their scope 3 supply chain commitments, targets and regulatory requirements for 2030 and beyond. The role of artificial intelligence in addressing decarbonization challenges Amid growing decarbonization challenges, AI technologies are emerging as powerful and accessible transformational tools, available at an increasingly affordable cost. With vast telematics data generated from cargo vehicles and shipping routes, AI can support operational centralization, optimize route planning, improve fuel efficiency and reduce emissions. In the freight logistics and commercial travel sectors, AI’s potential is pronounced because these networks inherently produce large amounts of actionable data. This data-driven environment is ideal for using AI to optimize variables such as vehicle loads, delivery routes and fuel consumption, all of which can contribute to decarbonization efforts. For example, AI systems may predict demand to minimize empty truck trips, optimize energy use in electric freight vehicles and anticipate maintenance to reduce energy inefficiencies. While freight logistics is a key area for AI integration, opportunities also exist in the passenger segment, particularly in aviation. Airlines manage large fleets and even small efficiency improvements, such as optimized flight paths, related to contrails for example, or predictive maintenance could lead to significant reductions in fuel consumption and emissions. Interviews conducted for this white paper revealed a growing recognition that many climate actions are “no regrets” measures that can enhance core business strategies by offering both cost savings and operational benefits. To see meaningful emission reductions in this decade, adopting AI interventions could be one of these “no regret” actions for the sector. Several executives interviewed for this report highlighted the technology’s potential to process large amounts of data, reduce computational times and turn data into actionable insights to accelerate productivity gains. Freight logistics companies have an opportunity to integrate AI into operations and customer experience strategies, among other areas, with the twin interconnected goals of improving efficiencies and reducing emissions. In the long term, AI could assist in structural changes such as planning efficient charging infrastructure for electric fleets as well as optimizing vehicle allocation, battery health and routing for all-electric autonomous vehicle fleets (already operational and growing in cities such as Phoenix, San Francisco, Los Angeles, Tokyo and Shanghai). As AI continues to develop at a fast pace, the significance of its impact is likely to grow well beyond 2030 – and the tools to start this journey are available now. Three key levers to deliver emission reductions AI offers a unique advantage – it can deliver incremental emission reductions without the significant upfront capital investments often needed to achieve deep decarbonization. This is particularly pronounced in contexts where high- capex decarbonization solutions – such as fleet electrification or green hydrogen fuel – can be challenging to implement and finance, or have limited availability. The maritime industry has seen a significant shift with about half of vessels now equipped with high-frequency data collection, a stark contrast to just 10 years ago. This advancement is a game-changer for AI’s applications in maritime transportation. Casimir Morobé, Founder and Chief Executive Office, Toqua There is a lot of untapped potential in AI applications. AI can identify complex patterns that may not be visible to the human eye. As AI matures, we can expect accelerated adoption. Key applications of AI such as route optimization and predictive maintenance are particularly promising and can be considered ‘low-hanging fruit’ for driving both operational efficiency and emissions reductions. Massimo Morin, Global Head, Travel, Amazon Web Services (AWS) for Travel and Hospitality Intelligent Transport, Greener Future: AI as a Catalyst to Decarbonize Global Logistics 8

Intelligent Transport Greener Future 2025