Amandeep Singh Gill
United Nations Under-Secretary-General and Special Envoy for Digital and Emerging Technologies
The convergence of global trade and AI combines the scale and complexity of cross-border exchange with the analytical and predictive capabilities of computational systems.
Trade generates diverse datasets on which AI technologies depend, while AI reshapes the efficiency and architecture of global commerce, shifting toward smarter, data-driven trade.
AI-powered trade evolution
Historically, trade facilitated the movement of goods, services and ideas across borders. Today, it facilitates the movement of intelligence. Each shipment, transaction and customs declaration contributes to a continuous feedback loop that enables systems to learn and improve. This evolution resembles the emergence of a learning network that spans regions and sectors.
Africa illustrates this clearly. The African Continental Free Trade Area hopes to integrate 54 economies into one market. Beyond policy harmonisation, participating states are building the digital public infrastructure for integration. These include interoperable identity services, cross-border payment networks and customs platforms capable of secure, efficient information exchange.
The Pan African Payment and Settlement System shows how these are reshaping commercial activity. Historically, cross-border payments within Africa were slow, costly and complex. Real-time settlement in local currencies reduced friction, especially for SMEs that depend on predictable transactions.
Embedding AI within trade systems produces more than operational efficiencies —
it expands participation, strengthens governance and opens pathways for inclusive development.
How AI amplifies improvements
Digital trade creates extensive data streams, including patterns in demand, logistical bottlenecks and regulatory inefficiencies. AI transforms data into insights that support decision-making. Smaller enterprises can now access analytical tools once available only to large corporations, while governments can test regulatory approaches using live data before applying them more broadly.
Examples are visible across the continent. Logistics providers use AI to forecast delivery times based on weather, traffic and road conditions. Digital trade finance platforms apply AI to enhance credit assessment, expanding capital access for businesses previously constrained by information gaps.
Embedding AI within trade systems produces more than operational efficiencies — it expands participation, strengthens governance and opens pathways for inclusive development. The promise lies in widening economic opportunity so that the circulation of intelligence supports shared and sustainable prosperity. This evolution signals a decisive shift in how nations cooperate economically, globally and effectively. Similar in scale to the 1970s shift to global supply chains in manufacturing, except this time, trade might reorganise itself around the data and AI value chains.
