Considering the escalating global geopolitical tensions and rapid advancements in artificial intelligence (AI) technology, understanding how these two factors shape investor behavior, market volatility, price discovery, liquidity, and systemic risk is vital for market stakeholders. The primary objective of this research is to provide an innovative conceptual framework that explains the complex interactions between geopolitical risk, economic-informational uncertainty, investor behavior, and the application of AI and algorithmic trading in financial markets.

The results of the analytical and critical literature review, alongside the examination of existing research on the study variables, indicate that geopolitical risk—by increasing insecurity and influencing investor perception—leads to heightened volatility, shifts in trading strategies, and contagion risk. Concurrently, AI and machine learning have become key tools for risk management and portfolio optimization due to their ability to process massive data volumes, identify complex patterns, and execute high-scale trades; they also possess the potential to influence price discovery and liquidity.

The proposed conceptual framework highlights the moderating and mediating roles of artificial intelligence in the relationship between geopolitical risk and market outcomes, while accounting for investor behavior. This research provides significant theoretical, managerial, and policy implications for investors, regulatory bodies, financial managers, and emerging markets, including the Iranian capital market.