Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Balaji, K. Title A name given to the resource Artificial Intelligence- Driven Business Intelligence for ESG Strategy Implementation: Enhancing Corporate Sustainability through Data-Driven Case Studies Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Data-Driven ESG Strategy Implementation Through Business Intelligence;pp.173-197 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-5142-1.ch007" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-5142-1.ch007</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105019016296?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105019016296?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Balaji K., CHRIST University, Bengaluru, India Description An account of the resource In the modern world of growing levels of stakeholder analysis and regulatory pressure, it has become a policy imperative of responsible companies to focus on the ESG (Environmental, Social, and Governance)- based considerations as an essential part of their central strategic effort. The main idea is to evaluate how the use of AI- powered BI tools allows achieving ESG data collection, analysis, visualization, and reporting, contributing to providing more responsible and intelligent decision-making in sustainability- focused organizations. The study follows a qualitative- type, multiple case study design, wherein the analysis of five practical entities representing various industries including energy, finance, manufacturing, and information technology. Information was gathered by conducting in- depth interviews with ESG officers and data analysts and the use of secondary data Results indicate that AI-assisted BI systems enable the ESG data to have a better granularity and a more timely and predictive nature, therefore, causing more responsive risk management and stakeholder engagement. 2026, IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833735144-5; 979-833735142-1; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online