IMF Chief Says Artificial Intelligence Offers Hope While Creating Risks for Global Leaders

Table of Contents

• You might want to know


• AI’s promise and the pressures shaping the global economy


• Key Insights Table


• Afterwards...

You might want to know

• How could artificial intelligence raise global growth while also adding to inflation and inequality?


• Why does the IMF chief see public debt and AI-related financial exposure as urgent risks for policymakers?

AI’s promise and the pressures shaping the global economy

Singapore — Artificial intelligence is increasingly viewed as a potential engine of economic expansion, yet it is emerging at a time when governments are also confronting high energy costs, inflation, and mounting public debt. Kristalina Georgieva, Managing Director of the International Monetary Fund (IMF), described this combination as a challenge to the already “underwhelming” growth recorded this decade. Speaking at an event in Singapore on Wednesday, she said AI is “rapidly becoming a key driver of countries’ relative fortunes in the world economy.”

Georgieva’s remarks came ahead of a series of IMF and World Bank annual meetings due to begin next week. She urged policymakers to stop postponing difficult decisions about debt and public finances. Her central message was that AI can create substantial opportunities, but the economic and financial environment surrounding its development makes the transition difficult to manage. “Love it, hate it, or fear it, AI is here,” she said.

She characterized the global economy as being pulled in opposing directions. The war in the Gulf, now in its eighth month, has produced what she called a “negative energy supply shock.” At the same time, the surge in investment related to AI is creating a “positive demand shock.” The effects of these forces, she said, are “highly uneven across the world,” meaning that the same global shift can benefit some economies while imposing significant costs on others.

On the positive side, investment in AI is expanding at a historically significant scale. As a share of gross domestic product, global AI investment is expected to reach, and likely exceed, the levels devoted to building railroads, electricity grids, or telecommunications networks. AI hardware and related technology products already represent more than a tenth of world goods trade, according to Georgieva.

The IMF estimates that AI could add up to half a percentage point to annual global growth if it is implemented effectively. Georgieva illustrated the possible scale of that change by comparing a growth rate of 3% with 3.5% over a decade. “Going from 3% to 3.5% over a decade — that is like adding an economy the size of ASEAN to the world economy,” she said. The comparison underscores why governments and investors see AI as more than a technology-sector development: its potential effects reach productivity, trade, investment, and national economic performance.

However, the potential gains are not expected to be shared equally. Economies with limited involvement in the global AI supply chain may receive fewer benefits from the investment boom. Georgieva warned that this imbalance could increase the risk of widening economic inequality across the globe. Access to infrastructure, skills, capital, and technology production may influence which countries can adopt AI widely and which remain on the margins of its growth.

The central tension is that AI may raise overall growth while concentrating its gains and adding new pressures to already fragile economic conditions. For policymakers, the task is therefore not simply to encourage investment. They must also consider how to broaden access to productivity gains, manage the transition for workers and businesses, and prepare for risks that arise as AI becomes more embedded in economies.

Inflation is one of the immediate concerns. Policymakers in the United States, Europe, and Asia have already been dealing with persistent price pressures. Georgieva said the AI construction boom is itself inflationary, while energy and food shocks, tariffs, and defense spending can add further upward pressure. Building data centers and expanding related infrastructure requires significant investment and resources, potentially increasing demand for equipment, energy, and other inputs.

Energy markets have been especially strained. Oil prices have remained above $100 per barrel as the Middle East conflict continues, with few signs of a diplomatic off-ramp. Retail diesel prices have also risen to record highs as limited refining capacity has tightened energy supplies. Higher fuel and energy costs can affect transportation, production, and household budgets, and can complicate efforts to bring inflation under control.

These pressures are reflected in financial markets. Bond yields in the United States, Germany, and Japan have surged to their highest levels in decades. Higher yields can make borrowing more expensive for governments and businesses, while also changing the value of existing financial assets. Georgieva noted that ballooning long-term private bond issuance by AI-related borrowers is competing with governments for capital. At the same time, some of the increase in yields may reflect expectations that faster growth could result from investment and technological progress.

The public debt outlook adds another layer of concern. Global public debt is near its highest level since World War II and is on track to soon exceed 100% of GDP. Georgieva described advanced economies as the “worst offenders.” For 17 years, governments benefited from what she called “a relatively easy ride,” because interest rates remained below growth rates. “Higher interest rates now put an end to that,” she said.

The relationship between interest rates and economic growth matters because it affects whether debt ratios can decline without governments taking additional fiscal measures. Georgieva said the interest-to-growth differential is now “much less favourable” and “set to climb higher.” As a result, the economic growth needed to reduce debt ratios without fiscal effort is “out of reach in the near term.” Governments may therefore face greater pressure to make choices about spending, revenues, investment, and debt management.

Financial strain is already visible in Europe, where spreads over German bunds are widening. This is happening not only for France and Italy but also for Ireland, Portugal, and other countries that reduced debt and deficits after the euro-area crisis. A series of shocks has increased public debt, while most countries’ fiscal deficits remain above pre-pandemic averages. Georgieva said “fiscal space is crying out for replenishment,” highlighting the need for governments to restore room to respond to future disruptions.

AI also brings risks within financial markets themselves. Strong corporate earnings have supported share prices and created wealth effects, but market confidence could become vulnerable if earnings disappoint. Georgieva cautioned that hyperscaler leverage and large, growing global holdings of U.S. equities could turn a setback into a far-reaching shock if company results fall short of expectations. This concern connects the technology boom to broader financial stability: a sharp repricing of AI-related assets could affect investors and institutions well beyond the companies directly building AI infrastructure.

Georgieva invoked Amara’s Law, which holds that people tend to overestimate the effects of a new technology in the short run and underestimate them in the long run. She suggested that the economy may be moving through the transition between today’s AI construction boom and the eventual arrival of AI’s wider benefits. In her words, it is during this transition that “we will traverse the period of maximum risk.” The timing matters because investment costs and market expectations may arrive before productivity gains are broadly realized.

Regulation and supervision, she said, should form the first line of defense. Effective oversight can help identify vulnerabilities, support responsible financial practices, and limit the chance that rapid investment creates risks that are difficult to contain. Georgieva also said that “now may be a good time for a prudently hawkish bias in many countries’ monetary policy.” This reflects the challenge facing central banks: they must weigh inflation risks against the possibility that tighter financial conditions could constrain growth and investment.

Taken together, her remarks describe a global economy with meaningful opportunities but little room for complacency. AI investment could improve productivity and raise growth, yet its benefits may be uneven, its infrastructure boom may add to inflation, and its financing may interact with high interest rates and already elevated public debt. Policymakers are being asked to address these issues at the same time rather than treating them as separate challenges.

Key Insights Table

Afterwards...

The coming years will test whether governments can translate AI investment into durable, widely shared gains while maintaining financial and fiscal stability. Research into productivity measurement, workforce adaptation, energy-efficient computing, and secure AI infrastructure could help clarify where the benefits are emerging and what costs accompany them. Better evidence would also enable policymakers to distinguish between temporary construction-driven activity and lasting improvements in output.

Further work is needed to understand how AI supply chains shape the distribution of economic opportunity between countries. International cooperation on access to skills, reliable digital infrastructure, and responsible technology standards may help economies participate more fully in the transition. Such efforts will not remove differences in national capacity, but they could make the benefits less dependent on a narrow group of producers and investors.

Financial authorities will also need to examine how concentrated exposures, borrowing, and market expectations interact as AI-related investment expands. Stress testing and transparent disclosure may help institutions identify vulnerabilities before they spread. At the same time, governments must consider credible approaches to restoring fiscal space, especially when borrowing costs are elevated and future shocks remain possible.

The key question is not whether AI will matter, but whether institutions can guide its adoption responsibly while preserving economic resilience. Continued exploration of AI governance, energy systems, productivity, public finance, and financial stability can help leaders make informed choices during the high-risk transition Georgieva described.