transform climate adaptation strategies in agriculture14 ( e. g. through optimized water use, early warning systems on invasions of alien species and selection of resistant crop varieties in response to climate change scenarios ) and in the insurance sector15 ( e. g. providing vast amounts of data to improve climate risk assessment and the pricing policies for climate - related damage protection ). bi, k. et al., 2023. accurate medium - range global weather forecasting with 3d neural networks, nature, 619, 533 - 538. lam, r. et al., 2023. learning skillful medium - range global weather forecasting, science, 382, 6677, 1416 - 1421. kyungmee, k. and boulanin, v., 2023. artificial intelligence for climate security. possibilities and challenges, stockholm international peace research institute. de baerdemaeker, j. et al., 2023. artificial intelligence in the agri - food sector, scientific foresight unit, european parliamentary research service. mclaughlin, m., 2022. climate change is a major challenge for insurers, but ai and cloud can help, ibm ibv blog. digital solutions can help with climate disclosure and climate - risk identification other areas in which digital innovation can help with climate transition are the assessment and selection of tools to channel funds towards green and sustainable finance, the progress in sustainability disclosure, the collection of climate - related information, and the evaluation and monitoring of climate - related financial risks, just to name a few important themes. let me briefly describe some of the efforts in these areas. first, the bis innovation hub and banca d ’ italia launched the g20 techsprint initiative in 2021, a global technological competition in the form of a long hackathon designed to show the potential for new technologies, new ( big ) data, and other innovations to leverage on the potential synergies between digitalization, finance and the energy transition. 16 another initiative in which banca d ’ italia was involved is the 2021 first call for proposals by the milano hub, the banca d ’ italia innovation centre located in milan. some of the projects developed under this umbrella showed how technology, and particularly ai, can contribute to improving financial services, in terms of esg data collection and production. 17 second, supply chain partners, financial regulators and financial entities increasingly require that companies, including small and medium enterprises ( smes ),

ai to map methane leaks from space, mit technology review, february 14, 2024. shaikh, m. and f., birajdar, 2024. artificial intelligence in groundwater management : innovations, challenges, and future prospects, international journal of science and research archive, 2024, 11 ( 01 ), 502 - 512. potentially also among economists like you. although at the moment these potential positive uses are still overshadowed by the large amount of energy required by digital technologies, this does not mean that researchers should not push the frontier in these areas. i will start by discussing ai - generated energy demand and supply as well as weather forecasts12 and how they can support climate mitigation and adaptation. i will then turn to the use of digital solutions to reinforce the green transition. ai can help with climate transition and adaptation ai solutions can foster the reliability of energy systems, deliver higher living standards, and ensure safety for populations and production. the power of ai possibilities is something we experience directly : nowadays smartphones and digital assistants provide a number of cheap and simple home automation solutions ; by coupling the internet of things ( iot ) with ai techniques, we can monitor and optimize the heating and cooling of our homes. outside of these day - to - day examples, however, there are many more ways that ai can be seen as a ‘ climate game changer ’. our smart - home solutions are just the tip of the iceberg. gaining a greater understanding of both when power is available and when it is needed is crucial to ensure the efficiency and reliability of the power grid, especially once an increasing share of intermittent renewable sources are integrated. the deployment of smart meters to collect information, and of digital technologies such as machine learning techniques for data analyses can lead to better forecasts of energy demand and supply, leading to improvements in energy efficiency. in addition, by supporting ‘ demand response ’, technology could minimize discrepancies between demand and supply, reducing ‘ peak loads ’ and the need to add capacity to manage those peaks, and in turn supporting the resilience and security of the energy infrastructure. in addition to enhancing energy demand and supply forecast and management, ai technologies can help improve weather forecasts as well as the early warning detection of acute climate events, which are essential tools for mitigating the impact of adverse events on populations and assets. progress in forecasting weather patterns and building climate scenarios could help vulnerable communities and authorities to adapt to climate change13 and could