Artificial intelligence could help cut emissions across sectors including energy, agriculture and buildings, but its climate benefits risk being outweighed by rising data centre emissions and water consumption, according to GlobalData.

The intelligence and productivity company said its latest report, Artificial intelligence for Climate Mitigation, found that AI can support targeted emissions-reduction efforts but cannot independently address the climate crisis.

It warned that the environmental costs associated with developing and using AI could outpace efficiency gains generated by the technology.

“AI can support climate mitigation, but it will never be the whole solution. For AI technology to have a net positive impact on the planet, the efficiencies it generates must outweigh the environmental harm caused by data centres and inference,” said Aoife McGurk, Senior Analyst at GlobalData Strategic Intelligence.

GlobalData said proven climate benefits from AI largely come from traditional predictive systems rather than energy-intensive generative AI and large frontier models.

 Predictive AI can improve renewable power-grid management, support sustainable agriculture and reduce energy use in buildings.

“Predictive AI can help improve efficiency and reduce resource use across key sectors, through renewable grid optimisation, sustainable agriculture, and building energy use management. Generative AI, on the other hand, produces significantly higher emissions, and there is little evidence that it mitigates climate change,” McGurk said.

The report also cautioned companies against relying heavily on generative AI, including large language models, for corporate sustainability strategies.

GlobalData said the technology’s carbon and water requirements, alongside the risk of inaccurate or fabricated information, could create compliance and reputational risks and potentially contribute to greenwashing.

GlobalData advised businesses to assess whether each AI deployment delivers measurable reductions in greenhouse gas emissions or ecosystem degradation and whether its environmental costs remain below its intended climate benefits.

“If a deployment of generative or agentic AI would deliver significant climate mitigation benefits, companies should do what they can to limit the environmental harm caused by using these systems,” McGurk said.

She recommended safeguards including smaller language models, automated model triage, carbon-aware computing, edge infrastructure, emissions budgets, greater algorithmic efficiency and improved data centre cooling to limit AI’s environmental impact. -OGN/TradeArabia News Service