How AI Is Reshaping the Global Economic Outlook

How is AI shaping the global economic outlook?

Artificial intelligence is increasingly moving from a technology-sector theme to a macroeconomic variable. In S&P Global Market Intelligence’s latest discussion of the global outlook, economists described AI as one of the forces helping to explain economic resilience in some regions, while also creating new sources of uncertainty for forecasts, financial markets and monetary policy.

The global backdrop remains fragile. Geopolitical risk, volatile commodity prices, sticky inflation and constrained public finances continue to shape the baseline outlook.

But alongside these headwinds, AI-related investment and trade are emerging as material offsets in parts of the global economy. The result is an outlook in which AI is both supporting near-term growth and complicating the assessment of underlying momentum, while also beginning to recalibrate expectations for labor demand and workforce planning.

Why is AI important for US economic resilience?

In the US, AI-related investment has become one of the clearest channels through which technology is affecting the real economy. Spending on data centers, computers, software and research and development began accelerating in early 2025, helping to offset slowing nonresidential fixed investment in other parts of the economy. Without that acceleration, underlying business investment would have looked considerably weaker.

AI is also influencing the US economy through financial markets. Since early 2024, a substantial share of the increase in the S&P 500 has been concentrated in a small number of AI-related companies. Higher equity valuations have lifted household net worth, supporting consumer spending through wealth effects at a time when higher prices and policy uncertainty are weighing on real income and confidence.

S&P Global’s PMI data provide additional evidence that this investment cycle is broadening beyond software and data centers into manufacturing. Economies central to AI development — including the US, mainland China, Japan, Taiwan, South Korea and the Netherlands — have recorded stronger manufacturing production growth than the global benchmark in every month since the end of 2025. The outperformance widened notably in the three months to June, while new orders also grew faster than the global average for five consecutive months.

That combination helps explain why the US economy has remained resilient despite historically high tariffs, elevated energy prices and uncertainty around trade and monetary policy. AI is not the only source of resilience, but it is increasingly important to understanding the composition of growth. 

How could AI affect US Federal Reserve policy?

AI’s implications for monetary policy are less straightforward. One of the Federal Reserve’s policy task forces is focused on productivity, jobs and inflation, including how AI could affect productivity growth, employment, the neutral interest rate and inflation dynamics. The potential policy implications depend on the timing, scale and macroeconomic transmission of AI-driven productivity gains.

If AI raises aggregate supply quickly, it could create room for monetary policy to support demand without reigniting inflation. But if productivity gains require substantial upfront investment, and if stronger productivity lifts the neutral real interest rate, the near-term case for lower rates becomes less clear. In that sense, AI is a policy wildcard rather than a one-directional argument for easier monetary conditions.

For forecasters, this means AI must be analyzed in the data rather than treated as an abstract theme. In the US, the effect is already visible in categories such as data centers, software, computers and R&D. It is also visible in household wealth through equity-market gains. Estimating the counterfactual — how the economy would look without the AI boost — is more challenging.

Labor-market evidence reinforces that uncertainty. S&P Global’s 2026 AI and labor research finds that businesses are still prioritizing process efficiency and employee productivity over head count reduction, with 64% of surveyed enterprises citing process efficiency and 59% citing employee productivity as AI objectives, compared with 24% citing head count reduction. Even so, the latest Purchasing Managers’ Index survey shows AI’s net global employment impact has shifted modestly negative over the past 12 months, with a further small negative impact expected in the coming year.

This distinction matters for monetary policy because AI may raise measured productivity before it produces broad labor displacement. Across 38 tracked AI use cases, the report finds average current adoption of 50% and planned adoption of 37% over the next year, but only 22% of AI projects target a fully autonomous end state. That points to a gradual shift in how work is organized rather than an immediate large-scale substitution of labor. 

Where is AI supporting Asia Pacific growth?

In Asia Pacific, the AI effect is showing up most clearly through trade and manufacturing. Strong exports in mainland China and across several regional economies have been supported by demand for AI-related and adjacent technologies. Economies that are highly integrated into technology supply chains have benefited from demand for semiconductors, storage, servers and other components linked to the build-out of AI infrastructure.

That export strength has helped offset weakness in domestic demand. In mainland China, AI-related and technology-product demand has supported export-oriented industries and investment, even as private consumption and property-sector activity remain soft. Across the region, AI-linked exports have provided a buffer against energy-price shocks and other external pressures.

The manufacturing data highlight how concentrated the AI boost remains. Taiwan reported the sharpest rise in new export orders among PMI-covered manufacturing economies in June, reflecting its dominant role in semiconductor production. The Netherlands also ranked near the top, supported by its upstream role in advanced chipmaking equipment and inputs. This suggests AI-related demand is benefiting not only end-product exporters but also economies positioned deeper in the capital-goods and semiconductor supply chain.

However, the quality of export growth matters. A key concern is that recent gains appear to be driven more by higher prices than stronger volumes. Semiconductor exports, for example, have seen sharp price increases while underlying volumes have risen only modestly. Shortages of critical components, higher freight and insurance costs, and longer delivery times also point to supply-chain constraints that could limit the durability of the export boom.

Sector-level PMI data point in the same direction. Technology Equipment, which supplies key AI-related hardware, posted the fastest expansion in output and new orders of all global sectors in June. Its production growth was the second-strongest in almost five years, helping lift the broader technology category to the top of the global sector rankings. 

Why has Europe lagged in AI-driven investment?

Europe has not yet experienced the same AI-related growth impulse as the US. Evidence of AI as a major driver of European investment in the first half of the year remains limited, and much of the AI investment taking place in Europe appears concentrated among large US-based organizations.

Several factors are holding back a broader AI investment cycle in Europe, including economic uncertainty, lower venture-capital investment and relatively high energy prices. These constraints matter because AI infrastructure is energy-intensive and capital-intensive, making financing conditions and power costs important determinants of adoption.

Even so, AI remains a potential upside risk for Europe’s medium-term outlook. Survey evidence points to meaningful, though uneven, AI adoption across EU firms. If investment conditions improve and adoption broadens, AI could become a more important driver of productivity growth, particularly in economies struggling with weak domestic demand and sluggish industrial activity.

What are the risks to the AI growth story?

The main risk is extrapolation. AI-related investment and exports are already supporting activity, but the scale and timing of productivity gains remain uncertain. Infrastructure spending can boost near-term demand before productivity benefits are fully realized. Export gains can reflect price pressures rather than healthy volume growth. Equity valuations can support consumption but also increase sensitivity to market corrections.

The labor-market risks are similarly nuanced. AI adoption remains broad, with common use cases such as summarization, translation and data management, but execution constraints are significant. S&P Global’s report notes that only 46% of AI initiatives launched in the past year are considered on track to achieve positive return on investment within 12 months, and only 37% are live and delivering value. Trust, data readiness and skills shortages could therefore slow the pace at which AI productivity gains translate into durable economic growth.

Supply-chain risks are also material. The AI build-out depends on semiconductors, servers, storage, data-center equipment, electricity and specialized inputs. Shortages or cost increases in any of these areas could slow deployment, raise prices and complicate inflation forecasts. For economies reliant on AI-linked exports, a moderation in global technology demand would create downside risk to growth.

The PMI data also reinforces the risk of geographic and sector concentration. The current manufacturing lift is strongest in a relatively narrow group of economies central to AI development and in hardware-heavy sectors such as Technology Equipment. If AI infrastructure demand moderates, or if bottlenecks in semiconductors, advanced machinery or data-center equipment intensify, the growth impulse could fade quickly in the economies now benefiting most. 

For policymakers, the challenge is to determine whether AI is changing the economy’s supply potential in real time or simply creating a temporary investment and valuation cycle. The answer will affect interest-rate assumptions, fiscal planning, industrial strategy, workforce development and the assessment of regional competitiveness.

The bottom line

AI is beginning to matter for the global economic outlook in measurable ways. It is lifting US investment, supporting equity valuations, reinforcing Asian export strength and driving manufacturing outperformance in economies central to AI development.

It is also changing how companies think about labor: Near-term adoption appears aimed primarily at augmenting workers and improving efficiency, but the employment impact has turned modestly negative and could become more material if autonomous use cases scale.

The AI cycle is no longer just a technology story; it is becoming an increasingly important macroeconomic, manufacturing and labor-market story.