Artificial Intelligence Trading Raises Concerns About Herding Behavior and Amplified Market Volatility, Adviser Warns of Need for Regulatory Adaptation

Digital Finance and AI-Enabled Risks Pose Challenges to Global Capital Markets

In a keynote address at the Global Securities Markets Conclave 2.0, Dr. V. Anantha Nageswaran, Chief Economic Adviser, highlighted the dual-edged impact of artificial intelligence on global capital markets. Advances in AI are fundamentally changing capital allocation, introducing new vulnerabilities that regulators must address.

AI's Benefits and Risks

AI lowers the cost of prediction, speeds up information processing, and enables decisions at unprecedented scale and velocity. It influences portfolio allocation, risk assessment, and liquidity management through algorithmic systems capable of learning continuously from vast data sets. However, this efficiency comes with risks, including a rising tendency towards herding behavior as global investors rely on similar AI models and respond rapidly to micro-information transmitted through digital and social platforms.

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Financial Stability Implications

According to the IMF's Global Financial Stability Report of October 2025, this herding behavior raises the possibility that financial cycles could become both longer and more amplified, with shocks transmitting quickly across borders. Algorithmic trading and AI-driven investment strategies can transmit shocks rapidly across jurisdictions and amplify market movements.

Regulatory Challenges

Supervisory frameworks need to evolve to detect model-based herd behavior, operational vulnerabilities, concentration risks in critical AI supply chains, and systemic feedback loops. As informational barriers decline, opportunities grow for economies demonstrating transparency, institutional credibility, and technological capability. However, this also raises policy responsibilities, emphasizing the need for regulators to stay ahead of embedded digital risks and ensure financial stability in the coming decade.

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