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IBM aims to achieve operational net zero GHG emissions by 2030 by leveraging AI-powered tools to manage energy data efficiently. The company plans to reduce current operational emissions through energy conservation and efficiency measures.
IBM si pone come obiettivo di raggiungere emissioni nette zero di gas serra operativi entro il 2030, sfruttando strumenti alimentati da intelligenza artificiale per gestire efficientemente i dati energetici. La compagnia prevede di ridurre le emissioni operative attuali attraverso misure di conservazione energetica e di efficienza.
IBM tiene como objetivo alcanzar cero emisiones netas operativas de gases de efecto invernadero para 2030 mediante el uso de herramientas impulsadas por inteligencia artificial para gestionar eficazmente los datos energéticos. La empresa planea reducir las emisiones operativas actuales a través de medidas de conservación de energía y eficiencia.
IBM은 2030년까지 AI 기반 도구를 활용하여 에너지 데이터를 효율적으로 관리함으로써 운영상 순 제로 온실 가스 배출을 달성하고자 합니다. 이 회사는 에너지 절약 및 효율성 향상 조치를 통해 현재의 운영 배출을 줄일 계획입니다.
IBM vise à atteindre des émissions nettes zéro de GES opérationnelles d'ici 2030 en utilisant des outils basés sur l'IA pour gérer efficacement les données énergétiques. L'entreprise prévoit de réduire les émissions opérationnelles actuelles à travers des mesures de conservation de l'énergie et d'efficacité.
IBM zielt darauf ab, bis 2030 netto null betriebliche THG-Emissionen zu erreichen, indem es KI-gestützte Werkzeuge nutzt, um Energiendaten effizient zu verwalten. Das Unternehmen plant, die aktuellen betrieblichen Emissionen durch Maßnahmen zur Energieeinsparung und Effizienzsteigerung zu reduzieren.
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NORTHAMPTON, MA / ACCESSWIRE / April 18, 2024 / IBM
IBM has set a target of reaching operational net zero GHG emissions by 2030 with 350,000 metric tons or less of residual CO2 emissions. This requires that we reduce our current operational emissions as much as possible through energy conservation - increasing operational efficiency and energy conservation and reducing energy consumption.
One of the key challenges is data. In sustainability, it's a popular saying that you can't manage what you don't measure. Jimmy McDonough, Global Energy Manager at IBM Global Real Estate, knows the key to address this - artificial intelligence (AI) powered tools.
In 2023, AI allowed Jimmy and other teams at IBM to capture and analyze IBM's energy data within a single, auditable tool across a portfolio of over 600 locations. With this, the company can pull reports and filter by location, geography, and utility, among others, to understand where energy consumption is highest, where there are unexpected changes in energy, and where the company has the most opportunity to drive energy conservation to help meet our 2030 net zero target.
For Jimmy and other IBMers, embedding this philosophy and strategy across the company's operations generates new insights that can create new energy conservation opportunities.
What is IBM's target for reaching net zero GHG emissions?
IBM has set a target of achieving operational net zero GHG emissions by 2030.
How does IBM plan to reduce its operational emissions?
IBM aims to reduce operational emissions through energy conservation, increasing efficiency, and reducing energy consumption.
What role does AI play in IBM's efforts to reach net zero emissions?
AI-powered tools are used by IBM to capture and analyze energy data across a portfolio of over 600 locations to identify energy conservation opportunities.
Who is Jimmy McDonough and what is his role at IBM?
Jimmy McDonough is the Global Energy Manager at IBM Global Real Estate, overseeing energy management strategies for the company.
How does IBM use AI to manage energy data across its operations?
IBM uses AI to capture and analyze energy data to understand energy consumption patterns and identify areas for energy conservation.
