INFLUENCE OF ARTIFICIAL INTELLIGENCE ON INVESTMENT DECISION MAKING IN GLOBAL FINANCIAL MARKETS

Abstract

The emergence of Artificial Intelligence (AI) as a transformative force in global financial markets represents one of the most significant developments in the history of modern finance. From algorithmic trading and machine learning-driven portfolio optimisation to natural language processing (NLP)-powered sentiment analysis and Robo-advisors, AI technologies are fundamentally redefining how investment decisions are made, executed, and evaluated across financial markets worldwide. This dissertation, titled "Influence of Artificial Intelligence on Investment Decision Making in Global Financial Markets," examines this transformation in depth. The study was undertaken as part of the MBA programme at Delhi School of Management, Delhi Technological University, under the guidance of Dr. Shikha N Khera, Associate Professor. The research is motivated by the recognition that while AI adoption in finance is accelerating at an unprecedented pace, comprehensive empirical research exploring practitioner perspectives particularly from the context of emerging markets like India remains limited. The primary objectives of the study are to examine the extent of AI adoption in investment decision-making, analyse AI's impact on investment performance and risk management, evaluate investor trust and ethical concerns regarding AI, assess the regulatory environment for AI in finance, and develop strategic recommendations for key stakeholders. The research adopts a mixed-methods design. Primary data was collected through a structured questionnaire survey administered to 85 usable respondents drawn from MBA students, investment analysts, portfolio managers, financial advisors, and academic researchers. The survey comprised 28 questions spanning awareness, usage patterns, perceived performance impact, ethical concerns, and regulatory preferences. Secondary data was gathered through a systematic review of over 35 peer-reviewed academic papers, 10 major industry reports, and 6 regulatory publications, covering the period from 2005 to 2024. Key findings of the study reveal that 88% of respondents are aware of AI applications in financial markets, and 72% currently utilise some form of AI tool in their investment activities. AI demonstrates its highest impact in improving the speed of investment analysis (mean Likert score: 4.52 out of 5) and portfolio risk management (4.12 out of v 5). While 67% of respondents believe AI has improved the overall quality of their investment decisions, significant concerns persist around model opacity (63%), data privacy (69%), and the creation of unfair advantages for large institutional investors (74%). The study concludes that the optimal framework for investment decision-making is a human-AI hybrid model, combining AI's computational superiority with human judgment's contextual nuance. It also finds that current regulatory frameworks are widely perceived as inadequate only 29% of respondents are satisfied with existing oversight. The study calls for mandatory explainability standards, robust algorithmic audit mechanisms, and dedicated AI-in-finance regulatory frameworks from bodies such as SEBI, the SEC, and ESMA. The report is organised into five chapters: Introduction, Literature Review, Research Methodology, Data Analysis and Recommendations, and Conclusion, followed by APA-formatted references and a detailed survey questionnaire annexure.