Generative AI, in particular, adds a new dimension. While this is an industry growth area, it can require substantial computational power and it also offers powerful capabilities to enhance decision-making, automate complex tasks and surface insights that drive more sustainable outcomes. When designed and operated with sustainability in mind – by measuring energy consumption baselines, optimising workloads, designing energy-efficient systems and sourcing cleaner energy – generative AI can unlock new efficiencies while mitigating its own energy use. We call this decarbonising growth. 

Last year, our Global Sustainability Barometer Study, which underscored AI’s growing impact in sustainability found that 55% of organisations believe AI will significantly affect their sustainability goals, yet many are not fully leveraging its capabilities beyond reporting and monitoring. This highlights the opportunity to scale AI-driven insights for more proactive, predictive decision-making. However, despite 80% of organisations acknowledging technology’s role in sustainability, only 32% feel they effectively harness its full potential. This signals a need for greater integration and adoption of AI-driven sustainability solutions.

Do the AI climate tools we need exist yet?

While many AI-powered climate tools exist today, we are still in the early stages of unlocking their full potential. We see advancements in AI-driven carbon accounting, emissions tracking and climate risk assessment tools. However, these tools must continue to evolve to provide more granular and accurate insights. A key challenge is ensuring the data they rely on is comprehensive, standardised and accessible to report externally. More collaboration is needed between policymakers, businesses and technology providers to refine these solutions and maximise their impact.