What type of study is this?

This is a Bibliometric Analysis study.

October 3, 2025

A bibliometric study on the role of artificial intelligence in enhancing investment decision-making processes

Puntos clave

AI technologies are enhancing investment decision-making processes, offering critical support in complex financial markets.
Over half of the research publications between 2015 and 2025 emerged in the last two years, with significant interest in AI's role in finance.
The study employed bibliometric analysis using Scopus data to map co-authorship and keyword usage, revealing interdisciplinary trends.
Emerging AI applications in algorithmic trading and portfolio optimization present both opportunities and gaps for future research.

Resumen

The rapid advancement of artificial intelligence (AI) has profoundly impacted various sectors, especially finance, where it has revolutionized how investment decisions are made. A bibliometric analysis of research publications from 2015 to 2025 highlights remarkable trends, with over half (51.7%) of all studies published in just the last two years (2024–2025), underscoring the field's explosive growth. Geographically, India has emerged as the top contributor, accounting for 28% of total publications, followed by the United States, China, and the United Kingdom. The interdisciplinary nature of AI research is evident in its subject distribution: Computer Science leads with 24.8% of publications, followed by Business & Economics (19.6%), Engineering (14.3%), Decision Sciences (12.7%), Mathematics (9.8%), and other fields making up the remaining 18.8%. AI technologies, such as machine learning and data analytics, are transforming finance by enhancing portfolio management, refining risk assessment, and enabling advanced predictive analytics. These innovations facilitate more efficient, data-driven investment strategies. Using the Scopus database and VOSviewer software, this study analyzes co-authorship patterns and keyword co-occurrence to map the field's landscape. The findings highlight key trends in AI applications for investment decision-making, particularly in algorithmic trading, risk management, and portfolio optimization. As global financial markets grow increasingly complex, AI-driven approaches offer critical support for decision-making, presenting both opportunities and challenges for researchers and practitioners. This bibliometric study sheds light on emerging trends, influential research, and significant gaps in the field. It provides valuable insights for researchers, practitioners, and policymakers seeking to understand AI's evolving role in shaping investment strategies and decision-making frameworks.

Preguntar a la IA

Me gusta

Guardar