Digital technologies offer significant advantages to help companies in their decarbonization efforts, specifically in operational efficiency, capital and carbon management. Three major value levers have emerged for data and AI applications. Operational efficiency: Generative AI enhances asset management and operational processes. By using predictive asset management, companies can: –Optimize production systems: AI helps streamline the entire production process, balancing output, margins and emissions. This boosts efficiency while minimizing energy use and emissions, directly supporting decarbonization. –Improve asset energy efficiency: AI enables better equipment monitoring, ensuring that assets run at peak energy efficiency, reducing both emissions and energy costs. Capital projects: Generative AI optimizes capital allocation and project management by: –Modelling energy transition scenarios: AI helps companies simulate various energy transition scenarios, enabling informed decisions on capital allocation for low-carbon and carbon-neutral projects. –Enhancing project design: AI can generate and refine capital project designs, reducing time-to-market and minimizing capital expenditure (CapEx) overruns. –Improving CCS: AI has the potential to lower CCS costs by up to 30%, according to the IEA.45 It enhances site selection for carbon storage through geological data analysis and optimizes CCS efficiency by monitoring the capture process. Carbon management: Generative AI supports carbon management and sustainability initiatives by: –Automating emissions management: AI tracks real-time energy consumption and optimizes energy efficiency at the equipment and process levels, reducing GHG emissions and lowering carbon footprints. –Managing carbon credits: AI automates the purchase and use of carbon credits, ensuring compliance with emissions regulations while maximizing green premium opportunities. –Decarbonizing the supply chain: AI continuously assesses suppliers’ carbon performance, helping companies choose low- carbon suppliers and reduce Scope 2 and 3 emissions across the supply chain. –Forecasting energy and emissions: AI predicts energy demand and deviations, allowing companies to take preventive measures to avoid higher emissions and align operations with sustainability goals. Despite its advantages, generative AI presents several challenges. The continuous operation of AI systems results in a constant peak demand for electricity from data centres, with projections indicating that their energy consumption could surpass 9% of total US electricity usage by 2030.46 Digital technologies offer significant advantages to help companies in their decarbonization efforts, specifically in operational efficiency, capital and carbon management. Net-Zero Industry Tracker: 2024 Edition 13

Net Zero Industry Tracker 2024 Cross Sector Findings