The rise of artificial intelligence (AI) tools such as ChatGPT has the potential to transform the global trading system by revolutionizing data analysis. While many industries adopted machine-learning tools during the pandemic, the trade sector struggled to catch up due to analog and paper-based transactions. However, the emergence of generative AI and language-learning models now presents an opportunity for governments and companies to better manage supply chains and mitigate risks.
Analyzing trade data has always been a complex task, with vast amounts of records scattered across various sources. AI tools are now helping organizations simplify this process and enable smoother cross-border commerce. Companies like ImportGenius are using machine-learning tools to recognize patterns in customs data, scan regulatory documents, and translate foreign languages, resulting in clear and accurate trade data. Multinational companies like Nestle and Mercedes-Benz are also adopting AI tools to increase efficiencies and detect emerging issues across their global value chains.
The application of AI in trade has significant advantages, especially as global barriers to trade such as tariffs and geopolitical uncertainties continue to rise. AI tools can help companies and governments better understand changes in global value chains. In fact, the recent Group of 20 (G20) trade ministers’ meeting endorsed a new mapping framework that uses AI to identify metrics related to supply chain resilience and help develop measures to mitigate external shocks. The International Trade Centre’s Global Trade Helpdesk is an AI-powered tool that matches trade data with predictive algorithms to assist companies and policymakers in refining their export strategies.
While there is a lot of promise surrounding AI in trade, it is important to separate short-term opportunities from wishful thinking. AI tools cannot replace human negotiations in trade agreements, as the human element is crucial in understanding the nuances of negotiations, body language, and informal ideas. Additionally, data accuracy remains a challenge for AI applications due to gaps and inconsistencies in trade statistics. Non-reported trade flows and political factors can affect the reliability of trade data.
Nevertheless, AI tools have the potential to revolutionize trade by improving supply chain management, enhancing data analysis, and assisting in decision-making processes. As organizations continue to adopt AI technologies, the future of trade and supply chains looks increasingly resilient and efficient.
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