AI can help companies move goods, clear customs and manage trade risks, but it cannot make global trade work smoothly on its own. The harder problem is coordinating rules, infrastructure and skills across borders so that businesses in different countries can use AI safely and share in its gains. That challenge is starting to change: firms are reporting benefits, AI-related hardware is reshaping trade flows, and customs authorities are exploring how to adopt the technology responsibly.
What “AI and global trade” actually means
The phrase covers three connected but distinct developments. Keeping them separate matters: activity in one area is not proof that the others are solved.
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- AI used to conduct trade: Businesses can use AI for supply-chain visibility, customs clearance, translation, market intelligence, contract enforcement and navigating regulations. These are practical applications, not evidence that every tool works equally well or is widely adopted.
- Trade in goods that enable AI: Semiconductors, servers and telecommunications equipment support AI infrastructure. Their growing trade is evidence of investment in AI-related capacity, not a measure of AI’s overall effect on trade.
- Rules and capabilities for AI across borders: Countries differ in their approaches to privacy, cybersecurity, competition and AI governance. Uneven digital infrastructure, workforce skills and customs readiness also shape who can participate.
The unresolved issue is therefore less whether AI can help with trade tasks and more whether countries and firms can connect those uses across different legal and technical systems without concentrating the gains among already well-equipped businesses.
Where firms see benefits—and what the evidence says
In a joint WTO–International Chamber of Commerce survey conducted in 2025, nearly 90% of firms that were already using AI reported tangible benefits in trade-related activities. Fifty-six percent of those AI-using firms said AI had enhanced their ability to manage trade risks. These are firms’ reported experiences, not results for all businesses or a controlled measure of AI’s effect.
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The applications help explain why firms see value. Better supply-chain visibility can help a company spot disruptions; translation and market intelligence can make it easier to assess overseas markets; and tools for customs or regulatory navigation may help teams handle complex procedures. But tools still depend on reliable data, suitable processes and people able to check the results. A system that performs well for one firm or route does not automatically transfer to another.
Why the cross-border problem is hard
Rules may not line up
Privacy, cybersecurity, competition and AI governance requirements can vary across jurisdictions. Differences may add compliance costs and make it harder for systems to exchange information or operate consistently. They also raise accountability questions when an AI-assisted decision affects a shipment, a customer or a regulatory obligation.
That does not mean every country needs identical rules. It does mean businesses and public agencies need workable ways to meet different requirements while preserving interoperability and clear responsibility.
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Access to infrastructure and skills is uneven
AI-supported trade requires more than software: businesses need digital connectivity, useful data and workers who can apply the tools. The WTO warns that unequal access to infrastructure and skills could leave smaller firms and economies with less digital capacity behind. If only well-connected companies can adopt the tools, lower costs and improved market access will not be shared broadly.
Customs agencies need readiness, not just technology
Customs authorities handle sensitive information and decisions that can affect safety, revenue and the movement of goods. Adoption therefore involves governance, resilience and data sovereignty as well as technical capability. On 1 June 2026, the World Customs Organization reported discussion of AI and machine-learning readiness tools and Mauritius’s experience adopting cloud services, including questions of data sovereignty and resilience. The account points to implementation considerations and peer learning; it does not report a quantified improvement in customs performance.
What is changing now
Trade in AI-enabling goods is growing
The WTO’s 2026 outlook reported that AI-enabling goods accounted for almost half of merchandise-trade growth in 2025, even though they made up one-sixth of total merchandise trade. That is a striking shift in trade flows, but it should be read as a finding about goods such as semiconductors, servers and telecommunications equipment—not as proof that AI has already made trade more inclusive or caused all of the growth.
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Customs discussions are becoming more practical
The WCO’s 2026 work reflects a move from asking only what AI might do toward assessing whether customs administrations are ready to use it. Readiness tools, governance and lessons from cloud adoption give agencies a way to examine prerequisites and risks before relying on new systems. The emphasis is on preparation and responsible implementation, not a claim that customs worldwide have already adopted AI.
Long-term projections point to opportunity, not certainty
WTO simulations in the 2026 executive summary project a 40% increase in global trade by 2040 and an addition of 12–13% to global GDP over a 15-year horizon. These are modeled outcomes, not observed results or guarantees. The WTO’s framing makes the conditions important: policy choices, infrastructure, skills and international cooperation influence whether potential gains materialize and who receives them.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What would make AI-enabled trade work for more people?
The useful test is not simply whether a company or agency has deployed an AI system. It is whether the surrounding conditions allow that system to support reliable, fair and compatible trade.
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- Build participation: Improve access to digital infrastructure and skills, including for smaller firms and economies with less capacity.
- Make systems work across borders: Reduce avoidable friction between rules and technical approaches, while keeping privacy, security and accountability in view.
- Assess public-sector readiness: Customs agencies need to consider data governance, resilience and sovereignty alongside technical tools.
- Measure the right outcomes: Report whether systems improve specific tasks and for whom, rather than treating AI adoption or rising hardware trade as proof of broad economic benefit.
The WTO’s “AI for Trade” work spans solutions, capacity building and knowledge, with a living set of case studies. That mix reflects the scale of the task: useful tools matter, but so do the skills and cooperation needed to put them to work across different markets.
The central challenge is coordination
AI is already being applied to trade, and firms using it report benefits. Yet the technology cannot by itself harmonize regulations, extend connectivity or make customs agencies ready. The change underway is a shift toward treating AI-enabled trade as a shared capacity and governance challenge—not just a collection of tools or a surge in demand for hardware.
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