Artificial Intelligence for Efficiency, Sustainability and Inclusivity in TradeTech

The report examines how AI is transforming global trade by streamlining supply chains, reducing trade finance gaps, and automating customs compliance. It contrasts 'AI convergence,' which would increase cumulative real trade growth by 13.6 percentage points, with 'AI divergence,' which could create 'trade islands' and exacerbate inequality. The document emphasizes that achieving widespread benefits requires international collaboration, interoperable standards, and public-private partnerships to overcome implementation complexities.

• The successful global implementation of AI, termed 'AI convergence,' could increase cumulative real trade growth in goods and services by 13.6 percentage points, whereas fragmented 'AI divergence' would only increase it by 9.3 percentage points and concentrate gains in 'trade islands'.
• AI enhances supply chain sustainability by enabling the measurement of Scope 3 emissions, which can represent 70% to 95% of an organization's environmental footprint, and by supporting circular economy models through predictive maintenance and automated recycling.
• In trade finance, AI is addressing a $2.5 trillion funding shortfall from 2022 by reducing credit decisioning times from approximately one month to less than one minute for some SMEs.
• AI improves customs and compliance by automating the classification of goods using Harmonized System (HS) codes, with some tools increasing automated classification accuracy from below 50% to 80% or more.
• AI is used to combat illicit trade and forced labour; for example, Project SEEKER detects illegally trafficked wildlife with over a 70% success rate for certain items, and AI tools help US Customs and Border Protection enforce the Uyghur Forced Labor Prevention Act.
• The adoption of AI in trade is influenced by the balance between the incentive for change and the ease of implementation; company-level optimizations like dynamic pricing are easier to implement than ecosystem-wide changes requiring primary data sharing.
• To achieve AI convergence, the report identifies four critical success factors: ensuring system interoperability, building trust through verifiability (such as Digital ID), facilitating public-private partnerships (PPPs), and investing in workforce development.
• The TradeTech Global Initiative, a partnership between the World Economic Forum and the United Arab Emirates, utilizes regulatory sandboxes to test AI and blockchain solutions in trade finance to inform international best practices.

APA

World Economic Forum (2025). Artificial Intelligence for Efficiency, Sustainability and Inclusivity in TradeTech. https://reports.weforum.org/docs/WEF_Artificial_Intelligence_for_Efficiency_Sustainability_and_Inclusivity_in_TradeTech_2025.pdf

Chicago

World Economic Forum. Artificial Intelligence for Efficiency, Sustainability and Inclusivity in TradeTech. 2025. https://reports.weforum.org/docs/WEF_Artificial_Intelligence_for_Efficiency_Sustainability_and_Inclusivity_in_TradeTech_2025.pdf.

Wikipedia

{{cite report |author=World Economic Forum |title=Artificial Intelligence for Efficiency, Sustainability and Inclusivity in TradeTech |date=January 2025 |url=https://reports.weforum.org/docs/WEF_Artificial_Intelligence_for_Efficiency_Sustainability_and_Inclusivity_in_TradeTech_2025.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{worldeconomicforum2025artificial, author = {{World Economic Forum}}, title = {{Artificial Intelligence for Efficiency, Sustainability and Inclusivity in TradeTech}}, institution = {World Economic Forum}, year = {2025}, month = jan, url = {https://reports.weforum.org/docs/WEF_Artificial_Intelligence_for_Efficiency_Sustainability_and_Inclusivity_in_TradeTech_2025.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }