What is AI's role in the climate transition and how can it drive growth?

The global economy is grappling with intensifying environmental crises, including climate change, biodiversity loss, and pollution, which call for urgent systemic transformation and a surge in climate and nature-related investments.

This transition requires significant investments – at least $4 trillion annually by 2030 globally, including $2.4 trillion in emerging markets and developing economies (EMDEs), where investment flows are lowest and potential for leapfrogging traditional technologies is greatest. For example, Africa holds 60% of the world’s best solar resources but received less than 2% of clean energy investments in 2023.

At the same time, growth is stuttering, and jobs and productivity are pressing issues across the world. A rapid response to the urgency and scale of investment now necessary for sustainability will also drive recovery and strong, efficient and clean growth, full of new opportunities. Thus, rather than being viewed as a cost, we must be clear that the net-zero transition can catalyze innovation, reduce inefficiencies, improve health, and stimulate inclusive growth.

Artificial Intelligence (AI), as a new, powerful, and dynamic general-purpose technology, is uniquely positioned to accelerate this transformation by scaling innovation and driving profound systemic change. Despite promising broad conceptual analyses, robust studies quantifying AI’s potential for macroeconomic growth and emissions reduction remain limited. Given the urgency and potential, there is a clear need for further exploration.

AI is a powerful enabler in five key domains critical to tackling climate change:

AI reimagines interconnected systems like power, transport, cities, and land use. In power systems, it improves grid stability and productivity by forecasting supply and demand and coordination across space and time, and integrating renewables and storage efficiently. For example, DeepMind’s wind energy optimization has boosted renewables’ economic value by 20%. These benefits are especially impactful in emerging markets with significant infrastructure gaps but enormous potential to leapfrog to cleaner systems.

Meeting net-zero goals requires not just scaling current solutions but also creating new technologies. The International Energy Agency (IEA) estimates nearly half of emissions reductions by 2050 will come from technologies not yet fully developed. AI accelerates discovery, as shown by DeepMind’s AlphaFold, which decoded over 200 million protein structures, unlocking advancements in areas like alternative proteins and energy storage. Digital speed is infusing science and technology.

AI empowers consumers to make climate-friendly choices through tailored interventions. Google Maps’ eco-friendly routing for example, uses AI to suggest routes that have fewer hills, less traffic, and constant speeds with the same or similar ETA. It has helped to prevent over 1 million tonnes of CO2 annually in its roll out phase in selected cities in Europe and the US —equivalent to taking 200,000 cars off the road.

AI enhances the precision of climate impact predictions and policy evaluations. Tools like IceNet and Google’s FloodHub process vast datasets in real time, providing early warnings for floods and sea ice changes. AI also predicts how policies like carbon pricing will influence behaviour, helping policymakers craft more effective interventions.

AI strengthens resilience to climate impacts by improving long-term adaptation strategies. For example, AI-powered drought forecasting, combined with canopy water content assessments, helps identify vulnerable regions. Such insights enable governments and communities to invest and manage the mitigation of risks more effectively, fostering stability and security.

In order to understand how the above factors may help accelerate technology adoption leading to emission reductions and more productive economies, we focus on three sectors – power, food, and mobility – which collectively contribute to half of global emissions and a corresponding fraction of world output.

Using sector-specific, historically based technology adoption curves (S-curves), we look at how AI – by improving efficiency, driving adoption of low-carbon technologies, and influencing behaviours – can accelerate these S-curves for key low-carbon technologies: solar and wind, alternative proteins, and electric vehicles.

What we find is that AI could accelerate adoption across these technologies and reduce annual emissions by approximately 3-6 gigatonnes of CO2-equivalent (GtCO2e) by 2035.

While these estimates focus on specific technologies and sectors, they do not account for dynamic cross-sector effects or potential rebound impacts.

AI also generates emissions through increased energy demand for data centres. Using best available estimates, we project that AI could add 0.4-1.6 GtCO2e annually by 2035. AI’s net impact on emissions therefore remains overwhelmingly positive, provided it is intentionally applied to accelerate low-carbon technologies. These are likely substantial underestimates of AI’s impact given that they capture only some of the dynamic and systemic effects and cover only part of the economy and emissions.

Market forces alone are unlikely to drive AI’s application toward climate action. Governments, tech and energy companies must play an active role in ensuring AI is used intentionally, equitably and sustainably. Together, they should:

With the support of civil societies, governments should also act as stewards of equity, ensuring that the Global South benefits from AI’s transformative potential, rather than being left behind. Without deliberate action, AI risks exacerbating global inequalities. The new opportunities and challenges from AI will re-shape public policies, provide interactions and the role and functioning of the state.

AI presents a unique opportunity to manage the climate crisis and accelerate the transition; in so doing it will drive innovation, growth, and resilience. Its ability to enhance, optimize, and reinvent systems, and accelerate discovery and innovation, can help align the global economy with net-zero goals. However, seizing this opportunity requires urgent, coordinated action from governments, businesses, and civil society working together and with markets.

Guided intentionally, AI can mitigate climate risks and build a more equitable and prosperous world. The challenge is no longer whether AI can contribute to the net-zero transition, but whether we will act decisively to harness its transformative potential with sufficient purpose and urgency.