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 Biju, Bertina Mariam Title A name given to the resource Aritificial intelligence in investment and wealth management 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 Applied Neural Networks in the AI Era: From Theory to Real-World Impact;pp.269-308 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-4571-0.ch010" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-4571-0.ch010</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105012223490?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105012223490?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 Biju B.M., Christ University, India Description An account of the resource Artificial Intelligence (AI) has emerged as a transformative force in various industries, revolutionizing the fields of investment and wealth management. This study explores how AI technologies, including machine learning, natural language processing, and robotic process automation, have enhanced decision-making processes, risk management, and portfolio optimization within financial services. Early developments in AI were limited by rule-based systems, but advancements in deep learning and access to large datasets have enabled sophisticated real-time analysis and personalized financial solutions. However, challenges related to data privacy, algorithmic bias, and ethical considerations persist, necessitating ongoing innovation in AI system transparency and accountability. This research analyzes the impact of AI on investment strategies, compares AI-driven portfolios with traditional approaches, and evaluates AI's role in reducing market volatility and improving return on investment. 2025, IGI Global Scientific Publishing. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833734573-4; 979-833734571-0; 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