How AI can Cut 5Gt of CO₂ by 2035 through Energy Efficiency
Artificial intelligence (AI) is no longer seen as a climate risk but increasingly as a vital tool in the global push for decarbonisation.
According to a 2025 study, titled Green and intelligent: the role of AI in the climate transition, led by Nicholas Stern and co-authors, AI has the potential to cut global emissions by up to 5.4 gigatonnes of CO₂ equivalent (CO₂e) annually by 2035.
This figure comes from emissions reductions projected in three core sectors: power, food and mobility.
Managing energy through smart systems
That level of savings not only offsets the emissions added by increased AI-related data centre energy use, but suggests AI could deliver a strong net benefit for the climate.
The report positions AI as a central enabler of global emissions reductions, capable of improving system-wide energy efficiency and supporting sustainable economic growth across a range of countries and development levels.
AI’s potential to optimise complex systems is particularly relevant to the energy sector.
Grid stability, increasingly challenged by intermittent renewables like wind and solar, can benefit from AI systems that forecast demand and manage distributed energy resources more effectively.
Singapore’s National AI Strategy provides an example of this in practice, as does Google DeepMind’s wind optimisation tool.
The latter boosted the market value of wind energy by 20% by better aligning power production with market needs.
Such tools not only improve performance but reduce the need for backup generation from fossil fuels, cutting overall emissions.
The report highlights how this type of system-level efficiency is becoming a cornerstone of AI’s climate role.
Access to finance for clean energy is another area where AI plays a part.
By improving risk prediction and aggregating diverse datasets, AI reduces information gaps that hold back sustainable investment, particularly in emerging markets.
Kate Brandt, Chief Sustainability Officer at Google, writes on LinkedIn: “The paper discusses the ways AI can play a powerful role in supporting climate action while boosting sustainable and inclusive economic growth.”
She adds: “Lord Stern spoke about three key sectors, power, food and mobility, which collectively contribute nearly half of global emissions and the ways AI can reduce their emissions.”
Boosting efficiency and materials innovation
A large share of the emissions reductions required by 2050 depend on technologies still in development.
AI helps accelerate innovation, such as through DeepMind’s GNoME tool, which has identified two million new materials with the potential to transform energy storage.
In heavy industry and logistics, AI improves energy efficiency and waste reduction.
Amazon has used AI to optimise packaging since 2015, saving more than 3 million tonnes of material.
At the same time, start-ups like GreyParrot are deploying computer vision to improve recycling processes, a key contributor to circular economy models.
These AI applications make industrial processes not only more productive but more environmentally sustainable, cutting waste and emissions throughout value chains.
Supporting behavioural shifts and climate resilience
Consumer-facing tools powered by AI are shaping how people use energy and resources.
Smart home systems such as Google Nest and Oracle Opower apply real-time data and behavioural science to help users cut their energy use.
In the food industry, AI applications such as Winnow Vision’s camera systems track waste and identify patterns in commercial kitchens, helping reduce food waste across more than 3,000 kitchens globally.
On the transport side, Google Maps now offers fuel-efficient route options, encouraging users to lower their emissions.
These kinds of tools influence daily decisions and can reinforce long-term shifts towards more sustainable lifestyles.
The report argues that behavioural change is critical to meeting global climate targets.
AI also improves the accuracy of climate modelling, supporting better policy-making.
IceNet, an AI tool for sea ice prediction, outperforms conventional systems in forecasting Arctic changes.
Similarly, Climate Policy Radar uses AI to analyse thousands of global climate policies, helping governments develop more effective regulation.
For climate adaptation, AI strengthens resilience infrastructure.
Google’s FloodHub offers five-day advance forecasts in 80 countries, helping reduce economic losses from floods.
Digital twin platforms, such as NVIDIA’s Earth-2, are also used to simulate extreme weather and long-term climate changes with greater precision.
Governance, equity and energy demand
Although AI presents clear opportunities, the energy implications of its expansion raise questions.
The report warns that letting market forces alone govern AI development could increase energy use and exacerbate inequality, particularly between developed nations and the Global South.
To prevent this, governments are encouraged to invest in equitable digital infrastructure, regulate data centre emissions and steer AI development towards climate-positive applications.
Public leadership, according to the report, will be essential to ensure AI benefits the widest number of people while aligning with long-term climate objectives.
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