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 AI-Powered Ergonomics: Transforming Workplace Health and Safety 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 Cases on AI Innovations in Occupational Health and Safety;pp.51-72 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-9301-7.ch003" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-9301-7.ch003</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105014459271?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105014459271?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 The integration of Artificial Intelligence (AI) into workplace ergonomics is revolutionizing the approach to employee health and safety. AI-powered ergonomic solutions leverage advanced data analytics, machine learning algorithms, and real-time monitoring to optimize workplace design, predict risks, and minimize injury-related costs. This article explores the transformative role of AI in identifying and mitigating ergonomic risks, particularly musculoskeletal disorders (MSDs) and repetitive strain injuries (RSIs), which remain prevalent across various industries. By using AI-driven wearables, motion sensors, and intelligent software, organizations can continuously analyze worker posture, movements, and environmental conditions, enabling proactive interventions. Additionally, AI models enable personalized recommendations for workplace adjustments, thereby enhancing employee comfort, productivity, and overall well-being. This article emphasizes how AI is reshaping workplace ergonomics, offering a datadriven, predictive approach to injury prevention and fostering a safer environment. 2025, IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836939303-1; 979-836939301-7; 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