Artificial intelligence, institutional quality, and carbon neutrality: a pathway analysis of OECD nations

Why smart machines and climate rules matter to you

Behind every online search, streaming video, or smart device lies powerful artificial intelligence that consumes vast amounts of energy. At the same time, the world is racing to cut greenhouse gas emissions and reach carbon neutrality. This article asks a simple but vital question: will AI help clean up the planet, or will it quietly make climate change worse? By looking at 35 advanced economies over three decades, the study shows that the answer depends not only on the technology itself but also on the strength of the institutions and rules that guide it.

Smart tools with a hidden energy bill

AI is often celebrated for its ability to save energy, predict weather patterns, and optimize transport and industry. It can help power grids match supply and demand, guide wind and solar farms, and track emissions in real time. Yet these smart systems run on giant data centers and complex models that demand enormous computing power. The study finds that, taken on its own, greater AI adoption is linked to higher carbon emissions in wealthy countries. In other words, the more these nations invest in AI without careful oversight, the more CO2 they tend to emit, largely because the energy used by digital infrastructure outweighs efficiency gains.

The quiet power of good rules and strong institutions

The key insight of the research is that strong institutions can flip this story. Institutions here mean the quality of laws, regulations, democratic checks, and the capacity of governments to enforce environmental rules. When the author examined the interaction between AI and institutional quality, a different pattern emerged. In countries with better governance, the combined effect of AI and strong institutions was a reduction in carbon emissions. Clear rules, transparent monitoring, and credible climate policies appear to steer AI toward cleaner uses and prevent abuses such as greenwashing or unchecked growth in energy use.

Tracing patterns across countries and time

To uncover these links, the study analyzed data from 35 OECD nations between 1990 and 2020. It tracked carbon emissions per person alongside measures of AI activity, economic growth, globalization, urban living, and an index of political and institutional quality. Using advanced statistical tools that follow each country through time, the author found an income pattern known as an environmental “inverted U.” As countries grow richer, emissions first rise and then eventually fall as cleaner technologies and stricter rules take hold. Within this pattern, AI alone pushed emissions up, but AI working together with strong institutions pushed them down.

When digital growth meets global change

The analysis also looked at factors such as globalization, shifts toward cleaner energy, and growing cities. The effects of these forces were mixed and often weaker than expected. Global ties showed a small tendency to lower emissions, possibly by spreading clean technologies and higher standards. Changes in energy systems and urbanization did not show a clear, consistent impact across all models. What stood out instead was the moderating role of institutions: where governments were more capable, transparent, and stable, AI was more likely to support emission cuts rather than fuel new pollution.

What this means for a low carbon future

For a general reader, the takeaway is straightforward. AI is not automatically good or bad for the climate. Left to grow without guidance, it tends to add to the world’s carbon burden by consuming more energy. When paired with strong rules, honest oversight, and long term climate goals, the same technology can help countries cut emissions and move toward carbon neutrality. The study suggests that to harness AI for a safer climate, societies must invest as much in good governance as they do in powerful algorithms.

Citation: Liu, J. Artificial intelligence, institutional quality, and carbon neutrality: a pathway analysis of OECD nations. Humanit Soc Sci Commun 13, 733 (2026). https://doi.org/10.1057/s41599-026-07098-y

Keywords: artificial intelligence, carbon neutrality, OECD countries, institutional quality, climate policy