Environmental Implications Of AI‑Enabled Algorithmic Trading: A Sustainability Perspective From Emerging Markets (India)

Abstract

Global financial markets are changing due to the quick uptake of algorithmic trading facilitated by artificial intelligence (AI), especially in developing nations like India. Although the majority of the literature focuses on how these technological changes affect liquidity, volatility, and efficiency, little is known about how they affect the environment. In order to place financial innovation within the larger context of sustainability, this paper provides a conceptual review of the environmental effects of algorithmic trading. It makes the case that the energy-intensive data centres, co-location facilities, and quick hardware turnover necessary for high-frequency and AI-driven trading lead to higher carbon footprints and the production of electronic waste. Drawing on evidence from studies in market microstructure (Hendershott et al., 2011; Hasbrouck & Saar, 2013; Menkveld, 2013), this paper reinterprets these findings through an environmental lens, with particular reference to India’s stock exchanges (NSE and BSE). The analysis highlights a tension between financial efficiency and environmental sustainability, underscoring the need for regulatory frameworks that integrate sustainable finance principles into digital market infrastructure. The study concludes by calling for interdisciplinary research that quantifies the ecological impact of algorithmic trading and proposes policy directions to align financial market modernisation with India’s climate and sustainability commitments.