Executive summary The freight logistics industry stands at a pivotal moment to significantly contribute to global decarbonization efforts. As a prominent source of greenhouse gas (GHG) emissions, the industry has the opportunity to align with the 1.5°C target set by the Paris Agreement. The substantial emissions gap, projected at 5.5 billion tonnes by 2050, underscores the urgency for innovative solutions. This report illustrates how artificial intelligence (AI) and machine learning (ML) can drive substantial and cost-effective decarbonization of global freight logistics now. The transportation sector, responsible for 16-25% of global GHG emissions, sees a significant portion (7-8%) coming from freight logistics. AI can be a powerful enabler to drive deep emission reductions by optimizing operations, enhancing capacity use and facilitating modal shifts. Analysis conducted for the paper suggests that three specific levers, outlined below, could reduce total emissions from freight logistics by 10-15%. Achieving operational excellence with AI –Route optimization and asset management: AI can achieve up to a 7% reduction in emissions through route optimization and efficient asset management. By leveraging real- time data and predictive analytics, AI ensures that every journey is as efficient as possible. –Improved capacity utilization: AI solutions address empty capacity issues by matching supply with demand and tackling market fragmentation. This improved capacity use can cut down on unnecessary trips and enhance overall operational efficiency, reducing emissions by up to 4%. –Modal shifts: AI can identify and implement the most carbon-efficient modes of transportation, shifting freight from, for example, road and air to rail or maritime options. This shift can reduce emissions by up to 4%.The potential for AI to drive sustainable practices in the freight logistics industry is vast. Companies adopting AI solutions now will not only meet emerging regulatory demands but also position themselves as leaders in a rapidly evolving landscape. Aligning corporate incentives with sustainability targets can drive meaningful change. Clear communication and demonstration of AI’s benefits, such as cost savings and operational efficiencies, can shift organizational and consumer mindsets towards embracing greener choices. Collaboration across the freight logistics ecosystem is crucial. By standardizing data formats and sharing best practices, stakeholders can optimize operations collectively. Partnerships between logistics providers, tech companies, regulators and governments are essential to drive systemic change. Establishing robust digital infrastructure and incentivizing sustainable practices among stakeholders are foundational for success. Public-private cooperation to enhance rail infrastructure, for example, can help create win-win scenarios for all involved. While AI offers immediate operational gains, a comprehensive approach that includes long- term strategies, such as investing in railroad infrastructure, fleet electrification and sustainable fuel adoption, is essential. Integrating AI now lays the groundwork for future technological advances and positions early adopters as industry pioneers. The tools for this transformative journey are available today and the benefits of acting now are clear: significant emissions reductions, enhanced efficiency and a competitive edge in an increasingly climate-conscious market. Some tangible actions and milestones can be adopted in this decade by various stakeholders in the value chain and the report highlights these next steps. Intelligent Transport, Greener Future: AI as a Catalyst to Decarbonize Global Logistics 5

Intelligent Transport Greener Future 2025