The World Trade Organisation (WTO) recently estimated that by 2040, artificial intelligence could lift global trade flows by almost 40 per cent and expand global GDP by 12-13 per cent. These are staggering figures-comparable to the arrival of containerization in the 20th century or the Internet revolution of the early 2000s. Yet, as I argue here, these forecasts are not destiny. They are conditional possibilities, shaped by how nations build infrastructure, regulate AI, invest in skills, and design ethical frameworks.
But there will be clear winners, losers, and the New Geography of Trade within this realm!
Winners.
Countries that have already invested in AI ecosystems, advanced R&D, and robust digital infrastructure will capture most of the upside. They will lead in semiconductors, cloud services, and high-end AI software exports. Small and medium-sized enterprises (SMEs) in digitally mature economies will also benefit, as AI translation, logistics, and compliance tools allow them to join global markets once reserved for larger corporations.
Losers.
But let us be candid-those without digital readiness risk further marginalisation. Economies reliant on low-skill, labour-intensive exports may see their comparative advantage vanish. Regions that remain disconnected from high-speed Internet and global value chains could be left outside this transformation. This creates the danger of a two-tier global economy: AI-rich versus AI-poor.
In 2023, global trade in AI-critical goods like chips and servers already exceeded USD 2.3 trillion, yet these are concentrated in a few geographies.
At the heart of this transformation lies infrastructure. AI-powered commerce is not simply about algorithms; it requires 5G and 6G networks, data centres, sovereign cloud platforms, and affordable computing power. In 2023, global trade in AI-critical goods like chips and servers already exceeded USD 2.3 trillion, yet these are concentrated in a few geographies. Export restrictions and tariffs on these goods-almost quadrupling between 2012 and 2024-only deepen dependency and exclusion.
Skills matter just as much. Without sustained investment in education, reskilling, and digital literacy, countries risk producing displaced workers rather than empowered innovators. The WTO has begun to position itself as a platform to discuss AI in trade, noting more than 80 AI-related trade concerns raised in recent years. But the global trade system was built for goods, not algorithms. We need new rules for data governance, cross-border AI services, intellectual property, and ethical use.
Equally worrying is the rise of digital protectionism and fragmentation. Export bans, data localisation mandates, and geopolitical rivalries could choke off the very flows of information that power AI. If unchecked, this will shrink the projected gains dramatically.
Several nations have moved from rhetoric to action by embedding AI into trade, logistics, and commercial policy ecosystems. China, for instance, has long placed AI and high-tech manufacturing at the heart of its industrial strategy (e.g. via the “Made in China 2025” framework) and is now intensifying its investments in AI infrastructure, data platforms, and smart manufacturing to capture more value in global supply chains. Meanwhile, India is pushing aggressively into AI-enabled digital services, fintech, and supply-chain automation – with central government initiatives such as the IndiaAI mission and consultations underway to establish AI safety and standards institutions. (UNCTAD notes that China, India, Brazil and the Philippines have all made measurable progress in harnessing AI for development). In the Gulf, the United Arab Emirates (UAE) has also staked its future on AI: launching a national AI strategy, creating data-centre hubs, and positioning itself as a regional technology hub.
These countries are pairing investment with regulatory foresight. For example, many trade agreements in the Asia-Pacific region are beginning to include AI provisions – by January 2025, 14 of 16 trade deals that mention AI originated in that region – reflecting a trend toward embedding AI governance in trade rules. In parallel, China and India are drafting and refining national AI ethics, data sovereignty, liability, and standards regimes to govern cross-border flows, data use, and algorithmic accountability. The aim is not just to adopt AI, but to ensure that AI-driven trade is trusted, resilient, and aligned with national goals. As more nations follow suit, the global architecture of trade will likely feature AI clauses, standards harmonisation, certification regimes and interoperability as fundamental building blocks rather than afterthoughts.
As someone deeply engaged with AI and fintech, I advocate for a trade future that is not only efficient but also equitable and ethical. Here are my guiding principles:
Equity by design. We must embed inclusivity into AI trade frameworks-open-source platforms, subsidised access in underserved regions, and global standards for fairness.
Strategic public infrastructure. Nations should invest in digital public goods-sovereign cloud systems, data commons, and public AI platforms-to prevent dependency on monopolistic providers.
Human capital first. Reskilling, educational reform, and continuous learning are non-negotiable if we are to prevent unemployment crises. Ethical and harmonised governance. Global standards for accountability, transparency, and liability are essential to build trust. AI in customs, payments, and trade finance must meet strict ethical benchmarks. Guard against fragmentation. Trade wars and digital barriers must be resisted. Cooperative multilateralism is the only way to unlock the 40 per cent trade boost. If we succeed, by 2040, we may witness AI-driven trade corridors where goods and services move seamlessly, supported by predictive supply chains, AI-enhanced customs, and real-time compliance systems.
If we fail, we may see a world of digital colonialism, where a handful of countries and corporations control the algorithms, while others remain locked out.
The WTO’s projections give us optimism, but they also give us responsibility. The AI trade boom must not replicate the inequalities of past globalisation. Instead, it should be the lever that delivers a fairer, more connected, and more sustainable world economy. As we stand at this inflexion point, I remain hopeful: with foresight, investment, and ethical resolve, AI can truly reshape global commerce-not just for the powerful few, but for the collective many.
The writer is Foreign Research Associate, Centre of Excellence, China Pakistan Economic Corridor, Islamabad.