Global economy under strain: how US tariffs + the AI boom are reshaping trade and markets

Global economy under strain: how US tariffs + the AI boom are reshaping trade and markets

For years, the global economy has relied on a simple story: lower trade barriers, more cross-border supply chains, and cheap digital technologies to knit it all together.

That story is now being rewritten.

On one side, the US has sharply escalated tariffs on Chinese goods and other imports, jolting global trade flows and supply chains. On the other, an enormous wave of investment in artificial intelligence (AI) infrastructure — chips, data centers, and cloud platforms — is propping up growth and reshaping who wins and loses in the world economy.

This article walks through what’s happening, why it matters, and who’s getting left behind.

1. The tariff shock: how US trade policy is stressing the system

From trade war to “structural break”

The US–China trade conflict that began years ago has hardened into a more permanent, structural shift in global trade.

A few key milestones:

Section 301 and subsequent tariffs: Over several rounds, the US imposed steep tariffs on a wide range of Chinese imports. China retaliated with its own levies and export controls, especially on critical inputs like rare earths.
Targeted green-tech tariffs (2024): In 2024, Washington announced new or higher tariffs on roughly $18 billion of Chinese exports, including electric vehicles, semiconductors, batteries, steel, aluminum, critical minerals, solar cells, and cranes.
Triple-digit tariffs (2025): By 2025, some analyses described US tariffs on many Chinese imports as effectively reaching around 100–145%, with China responding with tariffs of roughly 125% on a broad swath of US goods, although carve-outs exist for some strategic products like semiconductors and laptops.

Economists increasingly see these moves as a “structural break” in global trade — not a temporary spat, but a re-wiring of supply chains that will last years.

What tariffs do to trade and growth

Tariffs work through several channels:

Higher costs for importers and consumers
- US firms that rely on Chinese inputs face higher costs, and must either absorb them (lower profits) or pass them on (higher prices).
- Consumer goods — apparel, electronics, furniture, home appliances — risk becoming more expensive.
Supply chain disruption and diversion
- Companies try to “de-risk” by moving production from China to places like Vietnam, Mexico, and India, but recreating sophisticated supply chains is slow and costly.
- For key materials (like certain rare earths), China’s dominance makes short-term substitution extremely hard, amplifying vulnerability.
Hit to trade volumes and investment
- Trade wars create uncertainty: firms delay investment and new projects.
- Developing economies particularly suffer: they see reduced exports, weaker foreign direct investment (FDI), and more volatile currencies as investors seek safer markets.

Real-world evidence: Asia’s factories feel the pain

We can already see the effects on the ground:

In late 2025, factories in China, Japan, South Korea, and Taiwan showed persistent weakness, with purchasing managers’ indexes (PMIs) either contracting or barely expanding.
Export volumes for many Asian economies look better on paper, but manufacturers report that uncertainty around US tariffs and trade deals is still depressing new orders and business confidence.

At the global level, the IMF’s World Economic Outlook (October 2025) projects growth slowing from 3.3% in 2024 to 3.2% in 2025 and 3.1% in 2026, and explicitly notes that trade tensions and fragmentation are key downside risks.

So if tariffs are a drag, why isn’t the world already in a deep slump?

2. The AI investment boom: a powerful, but uneven, counterweight

Trillions for chips and data centers

Enter AI.

The race to build and deploy large AI models has unleashed a historic wave of capital spending:

Global data-center investment nearly doubled between 2022 and 2024, reaching around $0.5 trillion in 2024 alone, driven heavily by AI workloads.
Just a handful of US-based hyperscalers (Amazon, Google, Meta, Microsoft and others) are expected to spend more than $750 billion on AI-related capex over 2025–2026, mostly on data centers, GPUs, servers, networking gear, and related infrastructure.

One major newspaper described this dynamic succinctly: US tariffs jolted the global economy, but surging US AI investment is helping offset the shock, at least in the short term.

How AI spending props up growth

This is essentially a massive investment boom concentrated in a few technology-intensive sectors and countries:

Direct demand boost
- Construction of data centers, fabrication plants, and power infrastructure creates jobs and orders for steel, cement, electrical equipment, and services.
- Chipmakers, equipment suppliers, and cloud vendors see surging revenues, supporting stock markets and corporate earnings.
Productivity potential
- IMF and OECD research suggests that widespread AI adoption could raise productivity growth in advanced economies over the next decade, especially in the G7, as AI augments workers and automates routine tasks.
- If realized, these productivity gains would help offset the drag from trade fragmentation, at least for AI-leaders.
Spillovers through supply chains
- Semiconductor hubs in Taiwan, South Korea, Japan, and the Netherlands benefit directly from demand for advanced chips and manufacturing tools.
- Equipment makers, optical networking companies, and specialized construction and engineering firms also gain.

The result: even as tariffs weigh on trade, AI investment is injecting enough demand and optimism to keep global growth in the low-3% range, rather than collapsing outright.

But this rescue isn’t evenly shared.

3. Uneven global effects: AI haves vs. AI have-nots

Advanced economies and AI leaders

Countries best positioned to benefit from the AI wave tend to share three characteristics:

Strong digital and energy infrastructure
- They can host large data centers with reliable power and connectivity.
Deep capital markets
- They can finance huge, risky investments, often at low interest rates.
Skilled workforces and innovation ecosystems
- They have enough engineers, researchers, and tech firms to build on AI tools.

IMF and OECD studies highlight that advanced economies and a handful of middle-income countries with strong tech sectors are likely to see the largest productivity gains from AI, while others may lag.

In practice, that means:

The US remains the epicenter of AI development and capital spending.
East Asian tech hubs — notably Taiwan and South Korea — gain from surging demand for chips, components, and manufacturing equipment.
Certain European countries with strong semiconductor or equipment industries (e.g., the Netherlands, Germany) also benefit.

Emerging markets: mixed fortunes

For the rest of the world, the picture is more complicated:

Some Southeast Asian economies (e.g., Vietnam, Indonesia, Malaysia) are seeing increased manufacturing and export opportunities as firms diversify away from China. Their factory data in late 2025 shows comparatively better performance than North Asia.
India is benefiting from strong domestic demand and services exports and is actively trying to position itself as both an AI market and an alternative manufacturing hub.

However, many emerging and developing economies:

Lack the infrastructure (reliable power, data networks) to attract large AI-related investments.
Face higher borrowing costs, making it difficult to finance big technology or energy projects.
Depend on exports of low-value or commodity goods, which are more exposed to tariffs and trade disruptions and less likely to gain from AI productivity improvements in the near term.

The risk is clear: global inequality — between countries and within them — could widen, as AI accelerates growth in some economies while tariffs and fragmentation slow others.

4. Hidden costs: energy, infrastructure, and financial risks

AI’s growing energy footprint

The AI boom is not free — especially in terms of energy:

The IEA and private-sector research indicate that data centers’ electricity demand could increase by 50% by 2027 and as much as 165% by 2030, largely driven by AI workloads.
Local energy systems (grids, substations, cooling, water) in certain regions are already under strain, forcing new investments in generation and transmission.

This creates dilemmas:

Regions hosting data centers must balance AI growth with climate goals and local environmental constraints.
Higher energy demand can raise electricity prices or redirect power away from other uses if capacity doesn’t keep up.

Boom vs. bubble

Another concern is whether AI-driven spending is fully sustainable:

Forecasts suggest data center and infrastructure markets could approach $1 trillion by 2030, which is huge relative to past tech cycles.
A significant portion of this is being financed by big tech companies and their cash flows, but also by debt, equity issuance, and high market valuations.

If AI adoption disappoints — for example, if productivity gains are slower than expected or regulation bites hard — there is a risk of:

Overcapacity in some data-center markets,
Stranded assets in regions that over-build, and
Market corrections in tech valuations and corporate investment plans.

In short: AI capex is cushioning today’s tariff shock, but it may introduce new vulnerabilities of its own.

5. The bigger picture: fragmentation + tech race = a new global order

Pulling all of this together, we can see a few big themes.

1. From globalization to “bloc-based” trade

Tariffs, export controls, and security-driven industrial policies are pushing the world towards more regional or bloc-based trade.
Supply chains are being reorganized around trusted partners rather than pure cost efficiency, especially for strategic items — chips, batteries, rare earths, and clean-energy technology.

This will likely mean:

More redundancy (multiple suppliers) and higher costs,
Less pure efficiency, but potentially more resilience in crises.

2. AI as both shock absorber and amplifier

AI is playing a dual role:

Shock absorber: Investment in AI infrastructure has helped stabilize global growth in the face of tariff shocks, especially for economies at the center of AI supply chains.
Amplifier of divides: Because AI capabilities and capital are concentrated, the benefits are skewed toward a few countries and firms, potentially widening global and domestic inequalities.

3. Policy choices will determine whether this ends in renewal or fragmentation

Policymakers face a delicate balancing act:

On trade and tariffs
- Move from broad, blunt tariffs to more targeted, transparent, and predictable rules, especially for national-security-sensitive technologies.
- Support multilateral frameworks (WTO reforms, regional agreements) that limit escalation and give firms clarity.
On AI and productivity
- Invest in skills, digital infrastructure, and competition policy so AI benefits spread beyond a few giants.
- Help lower-income economies adopt AI tools and improve connectivity, narrowing the digital divide.
On energy and climate
- Pair AI data-center growth with massive clean-energy investment, grid upgrades, and efficiency standards.
- Avoid locking in high-carbon infrastructure just to feed AI’s electricity needs.

Done well, the AI era could offset some of the damage from trade fragmentation and even open new paths for inclusive growth. Done poorly, it could deepen divides and add financial and environmental stress to an already strained global system.

6. What to watch next

If you’re tracking this story, a few indicators are worth keeping an eye on:

Tariff and export-control announcements
- New measures on EVs, batteries, chips, and rare earths can quickly reshape trade flows.
AI capex guidance from big tech firms
- Quarterly earnings and capex plans from major cloud and chip companies are now macro-relevant data points.
Data-center and energy statistics
- Electricity demand growth in key hubs, grid-constraint news, and new clean-energy projects linked to AI loads.
IMF/OECD projections and stress tests
- Look for how they incorporate both trade fragmentation and AI-driven productivity in future scenarios.
Emerging-market performance
- Manufacturing PMIs, export data, and FDI flows in Asia, Africa, and Latin America will signal who is adapting — and who is falling behind.

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