{"id":8466,"date":"2026-07-15T09:42:02","date_gmt":"2026-07-15T01:42:02","guid":{"rendered":"https:\/\/moresourcing.com\/ai-can-measure-how-esg-really-impacts-the-bottom-line\/"},"modified":"2026-07-15T09:42:02","modified_gmt":"2026-07-15T01:42:02","slug":"ai-can-measure-how-esg-really-impacts-the-bottom-line","status":"publish","type":"post","link":"https:\/\/moresourcing.com\/de\/ai-can-measure-how-esg-really-impacts-the-bottom-line\/","title":{"rendered":"KI kann messen, wie ESG tats\u00e4chlich das Endergebnis beeinflusst"},"content":{"rendered":"<p><\/p>\n<div>\n<p class=\"Paragraph-module-scss-module__UwInRW__text\" data-first-paragraph=\"true\">K\u00fcrzlich haben wir beide vier weit verbreitete gro\u00dfe Sprachmodelle auf die \u00f6ffentlichen Offenlegungen von ExxonMobil angewendet. Das Ziel war nicht, einen weiteren ESG-Score zu erstellen, und es ging nicht darum, ExxonMobil herauszugreifen. Es ging darum zu testen, ob KI etwas tun kann, womit die Nachhaltigkeitsanalyse lange im gro\u00dfen Ma\u00dfstab gek\u00e4mpft hat: die Umwelt- und Sozialthemen, die ein Unternehmen selbst als finanziell relevant offenlegt, bestimmten Posten der Gewinn- und Verlustrechnung, Bilanz und Kapitalflussrechnung zuzuordnen und abzusch\u00e4tzen, wie starke oder schwache Leistungen bei jedem den Wert des Unternehmens beeinflussen w\u00fcrden. Einer von uns hatte diese Art von Analyse zuvor von Hand durchgef\u00fchrt. Es dauerte etwa 100 Stunden. Mit KI dauerte die gleiche Kernarbeit etwa eine Stunde; Teile davon wurden in Minuten erledigt.<\/p>\n<\/div>\n<p><script async=\"\" defer=\"\" crossorigin=\"anonymous\" src=\"https:\/\/connect.facebook.net\/en_US\/sdk.js#version=v19.2&amp;appId=1761258887507575&amp;xfbml=false&amp;status=true\"><\/script><\/p>\n<p>#Messen #ESG #Auswirkungen #Endergebnis<\/p>","protected":false},"excerpt":{"rendered":"<p>Recently, the two of us put four widely available large language models to work on ExxonMobil\u2019s public disclosures. The goal was not to produce another ESG score, and it was not to single out ExxonMobil. It was to test whether AI could do something sustainability analysis has long struggled to do at scale: take the [&hellip;]<\/p>","protected":false},"author":1,"featured_media":8467,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[9],"tags":[],"class_list":["post-8466","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-management"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.7.1 (Yoast SEO v25.8) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>AI Can Measure How ESG Really Impacts the Bottom Line - MORE SOURCING LTD<\/title>\n<meta name=\"description\" content=\"Advances in large language models are making rigorous sustainability analysis dramatically faster and cheaper, allowing investors and other stakeholders to connect companies\u2019 disclosed environmental and social risks directly to financial performance in a matter of hours rather than weeks. 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