Actions for freight logistics service providersIdentify quick-win use cases: –Start with AI use cases that are simple to implement, to build conviction and demonstrate savings; then scale-up from there to more complex initiatives. –Focus on quick-win, high-impact potential levers, such as operational efficiency gains that deliver rapid returns on investment while reducing carbon emissions. Build AI capabilities and an implementation roadmap: –Develop an AI implementation roadmap for the short to medium term. –Build a strong technological foundation by investing in training for relevant teams (e.g. strategy and procurement teams). –Create the right tech stack and introduce an actionable initiatives roadmap (including measurable KPIs). Seek cross-collaboration data-sharing opportunities: –Recognize that company-wide data can enable significant AI gains, but industry-wide data can unlock greater opportunities for emissions reduction. –Promote data-sharing and establish transparency in supply chain and process emissions, scheduling, congestion and routing data between key industry stakeholders (e.g. ports, ship operators, fleet owners, shippers and customers) to optimize operational efficiencies, load volumes and capacity utilization. Set up robust processes to measure carbon emissions: –Ensure mechanisms are in place to accurately measure the baseline for carbon emissions from operations. –Regularly measure and track carbon reduction associated with AI initiatives, AI use and the impact on operations. Actions for customers of freight logistics services (e.g. retailers) –Evaluate carbon intensity of the existing network: –Assess the carbon emissions within the existing logistics partner network. –Evaluate modal shift options to reduce carbon emissions and optimize cost in the process. –Apply AI tools for increasing transparency around the most rational and emission-reducing choices. Leverage demand power to accelerate decarbonization: –Encourage logistics service providers to increase the transparency of their sustainability strategies, especially short-term initiatives. –Consider making sustainability and/or AI-enablement a more central element of contract negotiations (e.g. a competitive dimension of RFP criteria) to incentivize transport operators to double-down on decarbonization. Communicate the full picture to enable customers to evaluate trade-offs: –Develop applications with AI that increase transparency about potential carbon emission impacts to empower customers to make an informed choice. –For example: display the environmental impact of same-day delivery compared to regular shipping via a more environmentally friendly mode. Actions for industry decision-makers, investors and stakeholders across the ecosystemExplore collaborative initiatives to accelerate AI solutions: Introduce support mechanisms, establish focus groups or identify investment opportunities to support AI implementation in hard-to-abate sectors. For example: pool knowledge – and potentially investments – via cross-sector sharing or even a green AI fund. Incentivize sustainable transportation: Consider incentivizing the sustainable transportation of goods and services through targeted programmes and funding opportunities. For example: incentivize the use of rail instead of road for transporting goods. Standardize processes: Explore opportunities to streamline trade processes and reduce cross-border challenges and delays. For example: align document formats regionally to reduce dwell/wait times, reducing fuel consumption. Collaborate on industry-wide standards: Develop responsible AI (RAI) usage and governance and provide guidance to operators for assessing and building AI trust and risk management capabilities, particularly as regulatory attention in RAI grows across many countries and regions of the world.Key actions for freight logistics providers, customers and stakeholders before 2030 TABLE 2: Intelligent Transport, Greener Future: AI as a Catalyst to Decarbonize Global Logistics 25

Intelligent Transport Greener Future 2025