BIS study warns AIās energy appetite is clouding interest rate signals
A new Bank for International Settlements paper says AI's climate footprint could blur the indicators central banks rely on to set rates
Central bankers already have a tricky job. They read the economy’s dashboard and decide where interest rates should go. A new study from the Bank for International Settlements suggests artificial intelligence is smudging the gauges.
The paper argues that AI’s environmental footprint, from rising electricity demand to strained power grids, could obscure the readings officials use to set policy. Those include capacity utilization and inflationary pressure, which carry real weight when rate decisions get made.
What the BIS paper actually says
BIS Paper No. 174 was published on October 8, 2026. Its authors are economists Leonardo Gambacorta and Salvatore Polizzi.
On the positive side, the authors credit AI with supporting both climate mitigation and adaptation. They point to gains in energy efficiency, better forecasting, and innovation in low-carbon technologies.
The paper warns 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 global data center consumption could exceed 945 terawatt hours by 2030, more than double current levels.
The paper also notes that AI’s energy intensity puts upward pressure on electricity prices and contributes to grid constraints.
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Why rate setters should pay attention
The authors argue that AI-driven changes in productivity and energy constraints could muddy the signals central banks depend on, including capacity utilization and inflationary pressure.
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? 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 a financial stability concern as well. The authors highlight the substantial investments flowing into AI infrastructure and energy generation. If those investments deliver disappointing returns, the study warns, 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, or AGI, the hypothetical point where AI matches broad human capability.
The authors say each scenario carries its own uncertainties for economic outcomes and policy implications.
Building on earlier BIS work
Prior BIS publications between 2024 and 2026 analyzed AI’s effects on economic growth, output, and inflation. Paper No. 174 extends that work 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.
What this means 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.
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.