The Asian Development Bank and UN ESCAP launched the Asia-Pacific Trade Facilitation Report 2026: Harnessing Artificial Intelligence in Trade Facilitation in Bangkok on 9 June 2026. Its message is more cautious than the title implies. AI is already changing how goods clear the region’s borders, but adoption is early, very uneven, and held back far more by people, data, and rules than by the technology itself.
Adoption is real, but early
The report’s anchor is the first joint ESCAP–ADB Survey on AI in Trade Facilitation, covering 48 economies. Region-wide, AI use in trade facilitation sits below 15%, with results running anywhere from 1% to 40% depending on where you look. East Asia leads on every measure the survey tracks: operational use, governance, capacity, and data quality. Australia and New Zealand come next, then Southeast Asia. The Pacific trails badly.
One finding deserves attention from anyone planning a rollout: having data is not the same as being able to use it. Many economies score well on data availability yet hold little of the standardised, interoperable data that production AI actually runs on.
Where AI already earns its keep
The report organises applications around the UN/CEFACT Buy–Ship–Pay model. At the Buy stage, AI drafts and checks trade documents and flags compliance gaps before a declaration is filed. At the Ship stage, it verifies documents, scores risk, detects anomalies, and reads inspection images, moving customs away from fixed rules toward targeting that adapts. At the Pay stage, it clears document-heavy trade finance faster. At every stage the report is firm on one point: because a wrong call carries legal liability, a human stays in the loop.
What is holding it back
The biggest obstacles are not technical. The survey puts a shortage of AI and machine-learning skills at the top of the list, followed by the cost of infrastructure, weak coordination between agencies, uneven data quality, and regulatory uncertainty. Model behaviour adds to the caution. Bias and hallucination are real problems, and an error rate that looks trivial becomes serious once an agency is processing millions of declarations a year.
What agencies want next
Asked about the next two years, surveyed agencies were specific:
| Priority area (next 2 years) | Share of agencies |
|---|---|
| Risk assessment and fraud detection | 68% |
| Document processing and verification | 64% |
| Capacity building and staff training | 45% |
| AI governance frameworks and policies | 35% |
| Data integration and interoperability | 34% |
To get there, the report sets out three pillars that reinforce one another: build human capacity and institutional readiness, build integrated data and digital infrastructure, and strengthen governance and regulation. It cites Singapore’s AI governance regime and its Networked Trade Platform as proof that clear rules can speed digital trade rather than slow it, and it presses for regional cooperation through the Framework Agreement on Facilitation of Cross-Border Paperless Trade in Asia and the Pacific (CPTA).
Summary
The promise is not in doubt. The WTO reckons wide AI adoption could lift global trade by as much as 37% by 2040. The gap is execution. With regional use still under 15%, Asia-Pacific is at the starting line, and catching up is a question of skills, usable data, and governance, not a procurement decision. The signal for business is plain: clean, well-governed documentation will move quickly through increasingly automated borders, while messy data will be stopped sooner.
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