Central bankers have a demanding job: reading the economy's dashboard and deciding where interest rates should go. A new study from the Bank for International Settlements (BIS), the Basel-based institution that serves central banks worldwide, suggests artificial intelligence is smudging the gauges. Because the BIS serves the very institutions that set rates, its research speaks directly to the officials making those decisions—giving this warning an immediate audience among policymakers.

The paper argues that AI's environmental footprint—from rising electricity demand to strained power grids—could obscure the readings officials rely on to set policy, including capacity utilization and inflationary pressure, both of which carry real weight when rate decisions are made.

What the paper says

BIS Paper No. 174 was published on October 8, 2026, and authored by economists Leonardo Gambacorta and Salvatore Polizzi.

The authors credit AI with supporting climate mitigation and adaptation, pointing to gains in energy efficiency, better forecasting, and innovation in low-carbon technologies. They also warn that AI systems—especially those housed in data centers—add significantly to electricity consumption and the emissions that come with it.

The International Energy Agency anticipates that global data center consumption could exceed 945 terawatt hours by 2030, more than double current levels—a scale that explains why the paper treats data center electricity demand as a macroeconomic variable rather than a niche technical issue. The paper adds that AI's energy intensity puts upward pressure on electricity prices and contributes to grid constraints.

Why rate setters should pay attention

According to the authors, AI-driven changes in productivity and energy constraints could muddy the signals central banks depend on. Is output climbing because the economy is overheating, or because AI made workers more productive? Are prices rising from excess demand, or because data centers are bidding up electricity?

The distinction matters because electricity prices feed into the inflation measures central banks target while capacity utilization is a classic gauge of how close an economy is running to its limits. Misreading an energy-driven price increase as broad overheating could push a central bank toward a policy move the economy does not need.

There is also a financial stability concern. The authors highlight the substantial investments flowing into AI infrastructure and energy generation, warning that if those investments deliver disappointing returns, they could pose risks to financial stability.

Two possible roads, neither fully mapped

The paper lays out two scenarios for how AI might unfold. The first is incremental, with AI gradually woven into markets and the wider economy. The second is transformative: a leap toward artificial general intelligence (AGI), the hypothetical point at which AI matches broad human capability. Each scenario, the authors say, carries its own uncertainties for economic outcomes and policy implications.

Building on earlier BIS work

BIS publications between 2024 and 2026 analyzed AI's effects on economic growth, output, and inflation. Paper No. 174 extends that line of research by adding climate to the picture, treating AI's energy use not as a side issue but as something that feeds directly into the economic signals policymakers watch. Framed that way, the paper reads less like a one-off analysis and more like a continuation of an active BIS research agenda on AI and the macroeconomy.

Implications for policymakers and markets

For central banks, the core message is that environmental effects belong inside traditional monetary policy frameworks. Treating AI's energy demand as a separate climate topic risks missing how it shows up in inflation and output data.

For investors, the paper points to a duality in AI adoption. The technology promises productivity and innovation, yet its energy costs could feed broader economic risks if power prices climb on data center demand. If energy costs add to inflationary pressure, central banks could respond with tighter policy.

What to watch from here is whether energy moves from the sidelines of monetary analysis toward its center: how central banks fold electricity prices and grid constraints into their reading of inflation and output, and whether the BIS extends its 2024–2026 research thread with further work linking AI, energy, and the economy.

The financial stability warning is worth keeping in view. Heavy spending on data centers and new power generation carries the risk of disappointing returns—and the BIS has now put that risk on the record.

Source: CryptoBriefing