International Journal of Environmental Sciences ISSN: 2229-7359 Vol. 11 No. 8, 2025 https://theaspd.com/index.php 976 The Role Of AI And Machine Learning In Portfolio Management: A Study On Engineering Faculties Investment Strategies In The Bangalore Region Mr. Naveen Kumar T S 1&2 , Dr. Sureshramana Mayya 3 1 Research Scholar, Institute of Management & Commerce, Srinivas University, Mangalore. 2 Assistant Professor, Department of MBA, Kalpataru Institute of Technology, Tiptur Orcid: 0009-0002-7946-0407, naveenkumarts22@gmail.com 3 Research Professor, Institute of Management & Commerce, Srinivas University, Mangalore. Orcid: 0000-0003-1951-0126, sureshmayya@hotmail.com Abstract: This study explores the impact of artificial intelligence (AI) and machine learning (ML) on the investment strategies of engineering faculty members in the Bangalore region. As financial markets become more complex, these technologies present significant opportunities to enhance portfolio management. The primary goal of this research is to examine how faculty members are incorporating AI and ML tools into their personal investment practices to improve portfolio performance, manage risks, and make informed decisions. Additionally, the study highlights gaps in knowledge, accessibility, and application of these technologies, offering important insights into areas needing further development. By conducting surveys and interviews, data will be gathered on faculty members' awareness, usage patterns, and trust in AI and ML-driven investment approaches. The research will evaluate their understanding of the advantages of using AI, such as real-time data analysis, predictive modeling, and automated decision-making, as well as the obstacles they encounter, including a lack of technical expertise or skepticism regarding the reliability of these tools. The findings from this study will help identify current challenges and provide actionable recommendations for improving the adoption of AI and ML in portfolio management among engineering faculty. These insights will also be useful for educational institutions, financial advisors, and technology developers in customizing AI solutions to better align with the investment management needs of academic professionals. This research will contribute to both the academic and investment sectors by bridging the gap between traditional investment methods and technology-driven solutions, ultimately enabling faculty members to make more informed investment decisions. Keywords: Artificial intelligence (AI), Machine learning (ML), Portfolio management, Investment strategies & Engineering faculty 1.0 INTRODUCTION The integration of artificial intelligence (AI) and machine learning (ML) across various industries has significantly transformed traditional practices, including portfolio management. AI and ML technologies have demonstrated considerable potential to reshape how investment decisions are made by processing vast amounts of data, identifying trends, and making predictions with speed and accuracy. These innovations enable investors to automate portfolio management, manage risks more efficiently, and optimize returns using real-time data. This study focuses on examining how engineering faculty members in the Bangalore region are incorporating AI and ML into their personal investment strategies and portfolio management[1]. Despite the growing availability of AI-powered investment tools, there remains a notable gap in their adoption and understanding, particularly among academic professionals. Faculty members, who may lack the time or financial expertise, can greatly benefit from AI and ML tools to enhance their investment management. However, barriers such as limited awareness, technical knowledge, or trust in AI may impede the effective utilization of these technologies. This research seeks to investigate these challenges by assessing the current practices, obstacles, and opportunities related to AI and ML adoption in investment strategies among engineering faculty members. Through this analysis, the study aims to provide recommendations to improve the adoption and application of AI tools in personal portfolio management for academic professionals. 1.0.1 Back ground of the study The financial sector has undergone a major transformation with the increasing integration of artificial intelligence (AI) and machine learning (ML) technologies, which have become pivotal in optimizing portfolio management. These technologies equip investors with advanced tools for real-time market