Similarly, the EU’s Technical Specification for Interoperability (ITS) defines the standards needed for seamless data exchange between operators, promoting rail system efficiency.31 In another example, the International Union of Railways (UIC) promotes rail transportation across regions through research and the development of technical standards. It brings together rail operators from different countries to establish common frameworks and ensure interoperability between national rail networks as they expand. UIC plays a role in creating standard technical specifications for rail equipment and promotes data-sharing protocols, ensuring that infrastructure development aligns with standardized data handling and communication systems globally.32 For the AI emissions opportunity to be captured, data standards and governance need to be embedded in global coalition conversations. Horizontal collaboration Horizontal collaboration within the freight logistics industry also faces challenges. Trucking companies, for example, often operate in highly competitive environments where sharing data and resources with competitors can seem counterintuitive or raise proprietary data security concerns. This competition can hinder the adoption of AI-powered solutions that require extensive data integration and cooperation to optimize routes, reduce empty miles and improve load factors. Additionally, the lack of standardized data formats and interoperability between different companies’ systems further complicates collaboration. Companies can be reluctant to share data, thinking of it as a competitive edge. However, data collaboration can unlock much wider benefits of AI. There is potential to create an industry-wide “data lake” with low-risk parameters to foster collaboration. To unlock the full potential of AI in reducing emissions, companies could overcome these barriers by establishing trust, standardizing data practices and creating frameworks for mutual benefit. The potential for collaboration between the industry, governments and tech platform providers is evident – with strong oversight to ensure that any concerns about anti-competitiveness are mitigated. There’s a lot of regional variation in preferences, policy, economic capacity and technological infrastructure. The future world could be even more of a patchwork of policies than today. Profound changes are unlikely to emerge from global consensus, which is getting harder to forge, but from places that are willing to lead with higher standards that set new benchmarks that spread widely. This fragmented approach, while not ideal, reflects the complex realities of international coordination and the diverse capabilities of different regions. David Victor, Professor of Innovation and Public Policy, Global Transformation Chair in Innovation, University of California, San Diego Data is most useful when abundant, but companies often think retaining it means retaining their power. There needs to be more data sharing for us all to be successful. Tobias Fischer, Deutsche Bahn, Tech and Innovation Intelligent Transport, Greener Future: AI as a Catalyst to Decarbonize Global Logistics 22

Intelligent Transport Greener Future 2025