Shaping the Future of Trade with AI
January 2026
1.Introduction
In today’s rapidly evolving world, international trade is more complex, fast-paced, and data-driven than ever. Artificial Intelligence (AI) is transforming how businesses and governments navigate this landscape, streamlining customs and logistics, analyzing markets, and managing trade finance. By processing vast amounts of data in real time, AI enables firms to respond quickly to shifting global demand, identify new opportunities, and remain competitive, while helping governments maintain secure and efficient trade flows. Yet, adoption is uneven, with regulatory, technical, and institutional challenges shaping who benefits most.
This blog delves into AI’s role in international trade, highlighting its practical applications across operations, finance, and market access. It also examines the barriers to adoption across countries and firms, setting the stage for a discussion on AI’s limitations and the policy measures needed to unlock its full potential.
2.What is AI?
AI is a technology that enables machines to simulate human intelligence, performing tasks such as learning, reasoning, problem-solving, and understanding language. While AI cannot fully replicate human cognition, it excels at analyzing large datasets, automating processes, and supporting decision-making. Key AI technologies include machine learning, deep learning, natural language processing, robotics, and expert systems. 1 2
AI’s impact on trade is amplified when combined with Blockchain and Internet of Things (IoT). Blockchain provides secure, transparent, and tamper-proof transaction records. IoT connects physical devices and sensors to collect real-time data on goods, logistics, and operations. Together with AI, these technologies create a smarter, more efficient, and reliable trade ecosystem, allowing better predictions, faster decision-making, and enhanced automation across global commerce.
3.What AI Can Deliver for Trade?
Before examining the specific applications and benefits of AI in international trade, it is important to consider the scale of its potential economic impact. Looking ahead to 2040, projections indicate that AI could significantly reshape the global trading system, with global trade volumes expected to increase by 34%–37%. Over
the same period, global GDP could rise by approximately 12%–13%, underscoring AI’s capacity to act as a powerful driver of long-term trade expansion, productivity growth, and global economic integration.3
ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ
1Trade Council, https://tradecouncil.org/wp-content/uploads/2024/10/artificial-intelligence-and-the-future-of- international-trade.pdf
2 Mdpi, https://www.mdpi.com/2227-7099/12/11/298
3 WTO, https://www.wto.org/english/news_e/news25_e/wtr_15sep25_e.htm?utm_source=chatgpt.com
· Applications of AI in Trade Activities
Firms are increasingly adopting AI to support trade compliance, regulatory checks, and risk management. Logistics companies, for example, use AI-driven platforms like the Descartes AI Suite to automate screening of shipments against export controls, sanctions, and product classification rules. 4 Customs authorities, such as
U.S. Customs and Border Protection, deploy machine learning–based systems to flag high-risk containers and suspicious declarations, helping detect smuggling, tariff fraud, and other violations.5
AI is also applied in contract analysis and trade finance to automate verification of documents, including invoices, bills of lading, and letters of credit. For market intelligence, AI-driven analytics process large volumes of trade data—covering prices, demand trends, and competitor behavior—while natural language processing tools facilitate multi-lingual communication in trade documents and negotiations. In logistics and supply chain management, machine learning models analyze historical and real-time data to forecast demand, optimize routes, and manage inventory. Additionally, AI supports customs operations by automating Harmonized System (HS) code assignment and tariff calculations. 6
Across these applications, AI’s ability to process vast amounts of information and generate predictive insights
contributes substantially to lowering trade barriers and improving competitiveness.7
ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ
4 Descartes, https://www.descartes.com/resources/news/descartes-showcases-global-trade-intelligence-technology-innovations#:~:text=ATLANTA%2C%20Georgia%2C%20February%206%2C,evolving%20tariffs%20and%20trade%20barrie rs.
5US Department of Homeland Security, https://www.dhs.gov/ai/use-case-inventory/cbp
6 UNCTAD, https://unctad.org/system/files/official-document/der2024_en.pdf
7 ICCWBO, https://iccwbo.org/news-publications/report/adopting-ai-for-trade-business-insights-to-inform-policy-and- practice/
· Benefits of AI in Trade-Related Activities
The practical applications of AI translate into tangible benefits across international trade systems. By improving efficiency, reducing costs, and strengthening risk management, AI is emerging as a key enabler of trade competitiveness in an increasingly complex global economy.
Building on this overview, the following sections examine in detail how AI delivers these benefits across three core dimensions of international trade: trade operations, trade finance, and market access.
1. Trade Operations
AI significantly improves trade operations by reducing costs and enhancing efficiency across the supply chain. Through machine learning and predictive analytics, firms can better align inventory levels with actual market demand, helping to avoid costly overstocking or stock shortages.
In logistics and transportation, AI plays an integrated role in optimizing both movement and asset management. AI- powered route optimization reduces shipping times and transportation costs by accounting for traffic conditions, weather disruptions, and geopolitical risks. At the same time,AI supports predictive maintenance by monitoring vehicles
and equipment through sensors and Internet of Things (IoT) technologies8. This proactive approach minimizes unexpected downtime, extends asset lifespans, and ensures more reliable and seamless trade operations.
AI also streamlines customs procedures by automatically analyzing large volumes of shipping documents, identifying compliance risks, and ensuring accurate product classification. By reducing human error and
ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ
8 The Internet of Things (IoT) refers to a network of physical devices, vehicles, appliances, and other physical objects that are embedded with sensors, software, and network connectivity, allowing them to collect and share data. https://www.ibm.com/think/topics/internet-of-things#:~:text=future%20of%20IoT-
,What%20is%20the%20IoT?,inventory%20and%20shipments%20in%20warehouses
accelerating customs clearance, AI helps minimize delays and improve overall operational efficiency. This is particularly important as AI managed to reduce global trade costs by 15% between 2000 and 2018.9
Beyond customs, AI automates repetitive operational tasks, including customer inquiries, inventory tracking, and order processing. This automation allows firms to reallocate human resources toward higher-value, strategic activities, leading to higher productivity, shorter processing times, and lower operating costs.
Finally, AI assists firms in navigating complex international trade regulations by accurately calculating tariffs and taxes, supporting classification decisions, and ensuring regulatory compliance. This reduces the risk of penalties, shipment hold-ups, and legal disputes, thereby enhancing overall business efficiency.
2. Trade Finance
AI-powered platforms can efficiently scan and validate financial documents, reducing administrative costs, minimizing human error, and accelerating transaction timelines. AI also strengthens risk assessment by analyzing large datasets—including financial records, and transaction histories—to detect patterns linked to financial instability or fraud. This improves lending decisions and enables more accurate risk profiling.
In addition, AI supports better cash flow management by forecasting future liquidity needs based on historical and market data, allowing firms to plan ahead and secure financing when needed. Finally, when combined with blockchain technology, AI improves transparency and trust in trade finance by enabling accurate transaction verification, reducing disputes, and strengthening confidence among trading partners through secure and immutable records.
3. Market Access
AI enhances market access by enabling firms to better understand consumer behavior, assess market dynamics, and design more effective market entry and expansion strategies. AI-driven analytics process large volumes of data—from social media, online reviews, market reports, and consumer behavior—to identify emerging trends, consumer preferences, and competitive conditions, helping firms target high-potential markets and choose appropriate entry strategies.
AI also supports more effective market engagement through communication. Machine-learning tools enable targeted marketing by segmenting consumers and tailoring messages, improving customer engagement and conversion rates. In parallel, AI-powered translation and natural language processing tools help overcome linguistic and cultural barriers, allowing firms to communicate more effectively across borders while capturing consumer sentiment.
Finally, AI enhances competitiveness and risk management by monitoring competitors in real time and assessing economic, political, and market risks associated with entering new markets. This enables firms to adjust strategies proactively, mitigate potential disruptions, and make more informed market entry decisions.
ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ
9WTO, https://www.wto.org/english/res_e/booksp_e/wtr25_e.pdf
· Case Illustration: Maersk
A prominent example of AI adoption in trade-related activities is Maersk, one of the world’s largest shipping and logistics companies. Maersk uses AI to optimize routing decisions, forecast demand, and improve container utilization across its global operations. These tools enhance operational efficiency and supply-chain resilience while also supporting environmental sustainability by reducing fuel consumption and emissions. The Maersk case illustrates how AI can simultaneously improve competitiveness, reliability, and sustainability in international trade.10
Despite these benefits, AI adoption remains uneven across countries and firms, reflecting disparities in infrastructure, skills, data availability, and regulatory readiness.
4. Limitations of AI Adoption in Trade Related Activities
The adoption of AI across international trade systems remains constrained by a complex set of limitations: Differences in regulatory frameworks, data governance regimes, and market conditions intersecting with high investment costs and technological constraints. Moreover, uncertainty surrounding returns on investment, gaps in digital and analytical skills, and persistent weaknesses in data quality and system integration further complicate AI adoption, especially for small and medium-sized enterprises in developing economies.
ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ
10 Mdpi, https://www.mdpi.com/2227-7099/12/11/298
Collectively, these limitations underscore that using AI in trade requires coordinated regulatory harmonization, capacity building, and supportive policy frameworks to unlock its full potential. 11 12 13 14
ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ
11 ICCWBO, https://iccwbo.org/news-publications/report/adopting-ai-for-trade-business-insights-to-inform-policy-and- practice/
12Academia,
https://www.academia.edu/44453775/Barriers_to_Adopting_AI_Technology_in_SMEs_A_Multiple_Case_Study_on_Per ceived_Barriers_Discouraging_Nordic_Small_and_Medium_Sized_Enterprises_to_Adopt_Artificial_Intelligence_Based_ Solutions
13 OECD, https://www.oecd.org/en/publications/artificial-intelligence-and-competitive-dynamics-in-downstream- markets_ccf0624a-en/full-report/component-5.html
14Wiley, https://onlinelibrary.wiley.com/doi/10.1111/jbl.12364
1. Bridging the Gap: What Can Policymakers Do?
To fully leverage AI in trade-related activities, it is essential to highlight policy recommendations that address key technical, regulatory, and social challenges:
- Enhancing data quality and accessibility:
Investing in robust data infrastructure and promoting standardized data formats by aligning national trade systems with international standards. Public–private partnerships can support data sharing across the trade ecosystem, while clear data-protection regulations are essential to safeguard sensitive information and build trust without slowing innovation.
- Promoting Ethical and Fair AI Use:
Governments and international bodies should establish clear ethical guidelines addressing bias, transparency, and accountability in AI-driven trade processes. Regular audits can help detect and reduce discriminatory outcomes, while well-defined responsibility frameworks are necessary to manage errors or harm caused by AI systems, ensuring that there are mechanisms for compensation when things go wrong.
- Reducing Technological Complexity and Costs:
Investment in education and training can help build a skilled workforce capable of developing and managing AI systems, while financial incentives such as grants, tax relief, and low-interest loans can encourage businesses—especially small and medium enterprises—to adopt AI technologies.
- Strengthening International Cooperation:
Harmonizing data-protection rules, aligning legal and ethical standards, and simplifying AI-enabled customs procedures can reduce barriers to cross-border trade. Collaboration between governments, businesses, and international organizations can also support the development of multilingual AI tools, improve supply-chain coordination, and enhance the ability to anticipate and manage geopolitical risks that disrupt trade.
No comment