The global economy is absorbing an unusual combination of shocks: an energy crisis linked to conflict in the Middle East, elevated public debt, volatile bond markets and an investment boom in artificial intelligence. For now, AI spending is helping prevent a sharper slowdown. But the same boom is also increasing financial fragility, leaving policymakers dependent on productivity gains that have yet to be fully demonstrated.
The International Monetary Fund has raised its 2026 global growth forecast, partly because companies continue to pour money into data centers, semiconductors and related infrastructure. That investment is acting as a counterweight to higher energy costs and weaker confidence. The effect is especially visible in technology-heavy economies, where capital expenditure has remained strong even as borrowing costs and geopolitical risks rise.
Yet the IMF’s message is not one of reassurance. It has warned that government bond yields could rise in a disorderly way as inflation, debt-service costs and AI-related borrowing place pressure on sovereign markets. Several advanced economies are already facing bond yields at multidecade highs, a development that can raise financing costs across households, companies and governments. CNBC reported that the fund sees the global economy as resilient but increasingly close to its limits.
Why AI is supporting growth
The immediate economic case for AI is straightforward. Building and operating advanced systems requires chips, electricity, construction, networking equipment and specialized services. Those purchases create demand before the technology’s longer-term productivity benefits are known. For suppliers and investors, the boom resembles an industrial build-out, with a small group of companies committing enormous sums to infrastructure.
This spending can support employment, tax revenue and business activity even if households remain cautious. It also explains why markets have continued to treat AI as a potential engine of expansion rather than merely another speculative technology theme. The optimistic view is that productivity improvements will eventually spread beyond the technology sector, allowing firms to produce more with fewer resources and helping governments manage aging populations and labor shortages.
That argument has political appeal. Governments want domestic AI capacity for economic competitiveness and national security, while companies fear falling behind rivals. Those incentives make a rapid investment cycle likely, regardless of whether near-term returns justify current valuations.
The risk of a narrow foundation
The vulnerability is concentration. Much of the growth impulse depends on a limited number of companies, investors and infrastructure projects. If expected productivity gains fail to arrive, spending could slow abruptly. The IMF has estimated that a disappointment in AI productivity could reduce global growth by 1.1 percentage points by 2028 and send U.S. equities down 20 percent, with Asia suffering an even larger hit to growth. The reported IMF scenario is not a forecast, but it illustrates how quickly optimism could become a financial shock.
There is also a physical constraint: electricity. AI data centers require large and reliable power supplies, while grids in many regions are already congested. Politico reported that Google has warned grid bottlenecks can delay new service for years as technology companies seek additional transmission capacity. That creates a feedback loop: AI investment increases energy demand, energy shortages push up prices, and higher prices feed inflation that limits central banks’ ability to cut interest rates.
Energy and geopolitics complicate the picture
The Middle East conflict has added another layer of uncertainty by increasing energy costs and forcing governments to balance inflation control with economic protection. Higher oil and gas prices transfer income from importing economies to producers, while also raising transport, food and manufacturing costs. Central banks facing renewed inflation may keep rates higher for longer, making heavily indebted governments more exposed.
At the same time, the AI boom is becoming part of geopolitical competition. States view chips, cloud infrastructure and computing capacity as strategic assets. Export controls and industrial subsidies may strengthen domestic supply chains, but they can also fragment markets and increase costs. Supporters argue that public investment is necessary to prevent dependence on foreign technology. Critics counter that subsidies may encourage wasteful duplication and reward politically connected firms.
What comes next
The next phase will depend on whether AI investment broadens into measurable productivity across the economy. Evidence of durable gains in manufacturing, services and public administration would validate current spending and ease fears of a bubble. Weak returns, delayed deployments or falling demand for computing capacity would expose companies and governments that borrowed on the assumption of endless growth.
Policymakers therefore face a difficult balance. They must preserve investment in infrastructure and research without treating every AI project as economically transformative. They also need to expand electricity networks, improve transparency around corporate borrowing and maintain credible fiscal plans. A disorderly bond-market adjustment would make both energy support and technology investment harder to finance.
The central lesson is that AI has not replaced the old sources of economic risk. It has temporarily masked some of them while adding new ones. The global economy may continue to expand, but its resilience increasingly rests on whether a capital-intensive promise can become broad-based productivity before debt, energy costs and geopolitical instability catch up.