Finance & Development – IMF
In this March 2026 article, Marcello Estevão analyzes the growing role of artificial intelligence as a driver of global economic activity. AI-related investment has become a major contributor to growth, particularly in the United States. However, the benefits remain uneven across sectors and regions. The article argues that while AI has the potential to boost productivity, its long-term impact depends on how effectively economies measure, finance, and manage this transformation.
AI investment and uneven global growth
Artificial intelligence is increasingly shaping economic performance. In the United States, AI-related investment contributes significantly to GDP growth, supporting demand for data centers, software, and energy infrastructure. As shown on the article, investment in information-processing equipment and software grew by 16.5 percent in 2025.
Despite this momentum, growth is uneven. AI-intensive sectors are expanding rapidly, while traditional industries such as manufacturing and construction lag behind. This creates a “two-speed” economy. A similar pattern appears globally. Growth in Europe and Japan remains stable but depends on supportive policies, whereas emerging markets benefit from capital inflows linked to technology investment.
Measurement challenges and policy risks
A key issue highlighted in the article is the difficulty of measuring AI’s true economic impact. Traditional national accounts were designed for industrial economies and do not fully capture intangible assets such as data, algorithms, and digital infrastructure.
As a result, official statistics may distort reality. GDP can overstate short-term growth by counting large capital expenditures while underestimating long-term productivity gains. This mismatch creates risks for policymakers. If economic conditions are misinterpreted, central banks may tighten or loosen policy at the wrong time. For example, rising electricity demand linked to AI infrastructure could increase inflation, even if underlying productivity is improving.
Global reconfiguration and capital flows
AI is also reshaping global trade and investment patterns. Demand for semiconductors, servers, and computing infrastructure is driving changes in supply chains. Manufacturing is shifting toward regions such as Southeast Asia and India, while specialized hubs in the United States expand production capacity.
This transformation reflects a new form of interdependence rather than a decline in globalization. Capital flows increasingly follow AI-related infrastructure, concentrating investment in a small number of firms and regions. As noted, large technology companies account for a disproportionate share of AI investment.
At the same time, differences in “digital depth” are becoming more important. Economies capable of producing and exporting digital goods attract more stable investment. Others remain dependent on imported technologies and volatile capital flows.
Diffusion, infrastructure, and long-term growth
The long-term impact of AI depends on its diffusion across the economy. Historical experience shows that general-purpose technologies generate productivity gains only after widespread adoption. While many firms are experimenting with AI, fewer have implemented it at scale.
Infrastructure constraints present an additional challenge. AI systems require significant energy and computing capacity. As highlighted in the article, global investment in data centers could reach $6.7 trillion by 2030. Energy bottlenecks and limited grid capacity may slow adoption and contribute to inflationary pressures.
The article concludes that AI has the potential to support global growth, but this outcome is not guaranteed. Its success depends on effective policy adaptation, improved measurement systems, and broader diffusion across industries.
Reference
Estevão, M. (2026, March). AI can lift global growth. Finance & Development, International Monetary Fund. https://www.imf.org/en/publications/fandd/issues/2026/03/point-of-view-ai-can-lift-global-growth-marcello-estevao