Artificial Intelligence for Efficiency Sustainability and Inclusivity in TradeTech 2025

Executive summary From enabling small firms to compete globally to making supply chains more sustainable, artificial intelligence’s (AI) impact extends far beyond efficiency gains. This report examines both how AI is currently being used in trade and the choices that will define its future effects. Concrete examples of AI use in supply chains, logistics, trade finance, and customs and compliance are presented throughout the report, demonstrating the range of benefits AI can unlock in terms of efficiency, sustainability and inclusivity. These include: –Opening new markets, particularly for small- and medium-sized enterprises (SMEs) –Enabling efficient automation –Enhancing supply-chain visibility –Promoting sustainability by supporting circular economy models and targeting carbon emissions for reduction –Strengthening the resilience and security of global trade However, these benefits may not extend throughout the entire trade ecosystem, depending on the extent to which AI is implemented. The successful implementation of AI across global trade, or “AI convergence”, can significantly increase real trade growth while enabling efficiency, sustainability and inclusivity gains across the trade ecosystem. The fragmented implementation of AI across global trade, or “AI divergence”, can increase real trade growth but concentrate the benefits of AI into “trade islands” – AI-powered hubs that offer superior efficiency but with limited participation. This could exacerbate global inequality in the short term, much as containerization initially benefited North-North trade more than other flows. Despite the incentives to use AI in trade processes, the difficulty of implementation threatens ecosystem- wide adoption. This report offers an actionable matrix, indicating the specific areas where AI adoption is more likely given its potential impact relative to its ease of implementation, highlighting areas where stakeholder incentives are aligned and areas where more extensive collaboration is required. Four factors can increase the ease of AI implementation in trade: 1. Ensuring system interoperability  2. Building trust 3. Facilitating public-private partnerships (PPPs) to align incentives  4. Investing in workforce development and digital infrastructure to strengthen human- AI collaboration  Achieving both rapid innovation and inclusive participation requires extensive collaboration and coordination across all parties in the trade ecosystem. Thankfully, AI can facilitate just that. AI is transforming global trade in ways that reshape both who participates and how business is done. Artificial Intelligence for Efficiency, Sustainability and Inclusivity in TradeTech 4