The growing global concerns regarding climate change, sustainable development, and corporate social responsibility have made green investment and Environmental, Social, and Governance (ESG) criteria among the most significant topics in the field of finance. At the same time, the increasing complexity of financial markets and the massive volume of structured and unstructured data have exposed the limitations of traditional portfolio management approaches.
The purpose of this study is to propose a novel Agentic Artificial Intelligence (Agentic AI)-based framework for the autonomous management of green investment portfolios, in which ESG data, market analytics, and quantum optimization models are integrated into a unified decision-making system. The proposed framework consists of a set of intelligent agents, including an ESG Analysis Agent, a Market Analysis Agent, a Risk Assessment Agent, a Decision-Making Agent, and a Quantum Optimization Agent. These agents collaboratively perform information gathering, market condition analysis, asset allocation, and portfolio rebalancing.
The theoretical findings of this research suggest that the simultaneous application of Agentic AI and quantum algorithms can enhance portfolio returns, reduce investment risk, and improve overall sustainability performance. By integrating autonomous decision-making capabilities with advanced optimization techniques, the proposed framework offers a promising approach for the next generation of sustainable and intelligent investment management systems.