Globalisation 2.0: How digital trade and AI are creating a new kind of interconnectedness

Whereas the initial wave of globalisation had been driven by ships, factories, and free trade agreements, the second wave — Globalisation 2.0 — is driven by data, digital services, and artificial intelligence.

Whether it is suggested movies from Netflix that are driven by algorithms in California or supply chains driven by AI that streamline deliveries in Singapore, the global economy is no longer just a question of the flow of goods and money — it's the flow of information.

But what does this mean for economies, governments, and consumers? And is this digital connectedness making the world more even — or uneven?

Globalisation 2.0 is defined by data flows, not shipping lanes.

Key Takeaways:

Data Is the New Trade Route: Digital trade — from streaming to AI analysis — now accounts for nearly 15% of global trade in services, according to the OECD.

The Rise of Digital Services Exports: In 2023, the UK alone exported over £180 billion of digital services — more than that of automobiles, machinery, or pharmaceuticals combined.

AI as a Productivity Engine: The IMF anticipates that AI will boost world GDP by 7% at the end of the decade but predicts increasing income inequality for high-skilled compared to low-skilled workers.

Regulation vs Innovation: Although electronic commerce has enhanced worldwide efficiency, a lack of mutual AI and data rules risks creating "digital divides" between countries. 

The next frontier: Digital trade and AI may reshape global power faster than industrialisation ever did.

1. What Is Globalisation 2.0?

Previous globalisation connected countries with physical commerce — products, goods, and people. Globalisation 2.0 connects them with information, digital platforms, and machine brains.

• In 2000, fewer than 400 million were connected.
• In 2025, over 5.4 billion will be connected (ITU, 2024)
• Border-crossing information flows nowadays generate more worth than trade in goods (McKinsey, 2024).

This means that a small app coder in Lagos can sell software to Berlin, or a Canadian artificial intelligence model help doctors in India — instantaneously.

But it also throws up difficult policy challenges:
How do governments tax digital trade? Who owns global data? And what happens to workers in industries that get automated with AI?

Data is now the fastest-growing form of international exchange.

2. Digital Economy Winners and Losers

Like every economic revolution, Globalisation 2.0 creates winners and losers.

Winners

• Technology Exporters: The biggest gainers are countries like the US, UK, South Korea, and Singapore, where 40–50% of all exports are digital services.
• Consumers: Variety and affordability of global digital goods — from streaming to e-learning — increase welfare.
• High-skilled Workers: Demand for digital consultants, data analysts, and AI engineers rose by 35% since 2020 (World Economic Forum, 2024).

Losers

• Low-skilled Workers: Automation threatens up to 40% of routine jobs in advanced economies by 2040 (IMF).
• Emerging Markets: Only 20% of Africans have reliable internet access, limiting digital trade participation.
• Tax Authorities: Governments are losing revenues from taxation as profits migrate online, often to low-taxing nations.

The shift toward digital value chains means that production, consumption, and profitability are no longer geography-bound — and therefore obsolescent taxation and trade policies no longer apply.

Digital exports are overtaking manufacturing as the driver of trade.

Economic Implications

• Economic Benefits: Businesses using AI in logistics have up to 25% lower operating cost (OECD, 2024)
• Inequality Effects: Technology companies make high profits with less staff, with wealth held by tech owners.
• Externalities: Automation makes workers more vulnerable to job loss but could increase productivity — repeating the "creative destruction" dynamic of the industrial revolution.

As a Year 13 economist I find that:

"Digital globalisation increases global efficiency — but also global inequality. The gains depend on how well countries adapt their human capital."

3. The AI Revolution: A New Global Connector

AI is not only transforming industries — it's redesigning the way nations depend on each other.

Global data streams form the foundation of machine learning algorithms.

A California-engineered chatbot might use Indian language information, UK healthcare data sets, and be based on Singapore servers.

This web of interdependence creates AI spillover effects — where technological innovation in one place raises productivity everywhere.

However the spillovers aren't evenly distributed:

• The US and China are ahead with over 70% of global AI investment (Stanford AI Index, 2024).
• The EU supplies much of the regulation innovation but lags on venture capital.
• Emerging economies suffer from data poverty — thin internet coverage, limited computing capacity, and minuscule digital markets.

This disparity may give rise to AI "superpowers" and AI "followers," echoing historical patterns of global inequality.

AI leadership is heavily concentrated in just a few economies.

Economic Perspectives

The World Bank estimates that integrating AI into global trade could boost total factor productivity by up to 1.2% a year — a boost to productivity on a par with the 1990s IT revolution.

But without inclusive investment, lower-income countries are subject to a "digital dependency trap", relying on imported platforms rather than building local capability.

4. Regulation vs Innovation

The tension nerve centre of globalisation has shifted to regulation.

Diverging Models:

• The EU AI Act (2024): Mandates severe transparency, risk classification, and accountability — prioritising ethics over speed.
• The US Model: Uses innovation, betting on corporate responsibility and minimal interference.
• China's Approach: Focuses on data sovereignty — data generated inside China should stay inside China — augmenting national strength at the expense of openness.

Economically, it creates regulatory fragmentation, where corporations need to comply with an array of usually opposing legal frameworks.

Startups have high compliance costs, while big firms can absorb them — securing market concentration.

The global challenge: regulating technology without slowing progress.

As one economics student might explain:

“Overregulation stifles innovation — underregulation destroys trust. The challenge is finding the equilibrium where digital growth is sustainable.”

There’s also a geopolitical element.

Countries that set AI and data standards (like the EU with the AI Act) gain “rule-making power”, shaping how the world trades and uses technology.

5. The Future: A New Global Balance

AI and digital trade aren’t just reshaping industries — they’re reshaping global power.

Forecasts (OECD, 2025):

• Early investments by emerging economies in digital infrastructure may make GDP 1.5× higher than that of late adopters.
• AI education nations may boost world GDP by $2 trillion a year by 2035.
• But digitisation failures by nations may lead to high unemployment and capital flight.

Global Challenges Ahead

• Digital Fragmentation: Compelling standards may fragment the international internet into regional "data blocs."
• Cybersecurity Threats: Greater interconnectivity exposes economies to digital threats.
• Ethical AI: Algorithmic bias can lock in inequality or distort trade outcomes.

A well-globalised AI economy will rely on international coordination — just as postwar institutions steered industrial trade.

The next global divide: digital readiness.

6. My opinion

As a Year 13 economics student, I see Globalisation 2.0 both as a huge opportunity and a clear risk.

Artificial Intelligence and e-commerce are connecting us quicker and smarter than ever before — but leaving others behind.

Unless we invest in digital skills, education, and fair policy, the gap between the winners and losers will expand.

The policy challenge is clear:

• Foster innovation.
• Invest in digital literacy and capacity.
• Design fair, global AI and data frameworks.

If the first globalisation was about ships moving goods, the second is about bits moving ideas.
How we make that leap will determine not just who gets richer, but who gets connected.

The future of globalisation is already online.