The world has entered a moment where algorithms quietly decide which ships dock first, which factories scale fastest, and which workers are left scrambling to catch up. Artificial intelligence and automation are no longer futuristic concepts debated in academic circles-they are active forces reshaping global trade, productivity, and power. The real question confronting policymakers today is not whether AI will transform the global economy, but who will benefit from it-and who will be left behind.
In boardrooms from Shanghai to Silicon Valley, AI is being celebrated as the ultimate productivity engine. In ministries from Islamabad to Brasília, it is viewed with a mix of hope and apprehension. That tension is justified. History shows that every technological revolution creates winners and losers, but AI’s speed and scale make this transition uniquely disruptive. Unlike past waves of mechanisation, AI is not only automating manual labour-it is automating cognition, logistics, finance, and decision-making itself.
According to estimates cited by the International Monetary Fund, AI could add around 0.3 percentage points to global GDP growth annually by 2026, with medium-term gains potentially much higher if adoption accelerates. But aggregate growth figures mask a deeper reality: AI-driven growth is becoming highly concentrated-geographically, technologically, and institutionally.
Nowhere is this more evident than in global trade. The old logic of comparative advantage-cheap labour, scale manufacturing, and export-led growth-is being rewritten. Today, value increasingly lies in semiconductors, data centres, cloud infrastructure, and algorithmic control of supply chains. The World Trade Organisation notes that trade growth in AI-related goods-advanced chips, automation equipment, and precision electronics-has outpaced traditional manufacturing categories, even as overall trade volumes slow under geopolitical strain.
This shift favours countries already embedded in advanced innovation ecosystems. The United States, China, parts of the European Union, and a handful of East Asian economies dominate AI patents, computing capacity, and semiconductor fabrication. Meanwhile, many developing economies risk being locked into a new form of dependency-consumers of AI technologies rather than co-creators of them. Automation may reduce their labour-cost advantage before they can climb the value chain.
AI and automation will not end globalisation, but they are unquestionably re-wiring it.
The labour implications are equally complex. Contrary to alarmist narratives, AI is not triggering mass unemployment overnight. Studies referenced by the Organisation for Economic Co-operation and Development suggest that in the near term, AI will restructure jobs more than eliminate them. Yet restructuring is not neutral. White-collar roles-accounting, procurement, logistics planning, even legal research-are increasingly exposed. Without aggressive reskilling, entire segments of the middle class could face downward mobility.
Global thinkers are divided. Economist Jeffrey Sachs argues that AI can be a powerful equaliser if paired with smart public investment and global cooperation. Others warn that in a fragmented world-marked by export controls, tech sanctions, and strategic rivalry-AI may deepen inequality between nations and accelerate the formation of rival economic blocs.
From my perspective, the danger lies not in AI itself, but in policy inertia. Too many governments are still debating AI ethics while neglecting AI economics. Nations that fail to invest in digital infrastructure, applied research, and workforce transformation will not merely fall behind-they will become structurally irrelevant in future trade networks.
For countries like Pakistan and much of the Global South, the path forward is narrow but navigable. AI must be treated as an industrial policy, not just an IT upgrade. This means embedding AI into energy efficiency, agriculture, logistics, climate adaptation, and manufacturing-not importing finished solutions, but building local capability. It also means aligning education systems with data, automation, and systems thinking rather than rote credentials.
AI and automation will not end globalisation, but they are unquestionably re-wiring it. Trade will move less in containers of cheap goods and more through invisible pipelines of data, chips, and algorithms. The nations that understand this shift-and act decisively-will define the next economic era. The rest will watch it unfold from the margins.
The choice before us is stark: use AI to broaden prosperity, or allow it to harden a new global divide. Technology will not decide that outcome. Policy will.
The writer is Foreign Research Associate, Centre of Excellence, China Pakistan Economic Corridor, Islamabad.