International Journal of Technology and Applied Science

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Volume 17 Issue 7
July 2026

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From Reactive to Anticipatory: Agentic AI Systems for Pre-Emptive Risk Detection in Volatile Power Sector Stocks

Author(s) Ms. Diptimayee Dash, Mr. Kirankumar Balagi
Country India
Abstract The financial markets, particularly India’s power sector, are increasingly susceptible to multi-layered risks arising from regulatory shifts, geopolitical tensions, commodity price volatility, and policy reversals. Traditional reactive investment strategies which respond to risk only after it manifests in price have proven inadequate for protecting retail and institutional investors alike. This study introduces the concept of Agentic Artificial Intelligence (Agentic AI) as a paradigm shift from reactive to anticipatory risk management in stock investment decision-making. Drawing on a primary survey of 200 individual investors across India with exposure to NSE-listed power sector stocks (Adani Power, Tata Power, NHPC, and NTPC), this research develops and validates a six-construct Structural Equation Model (SEM) examining the interplay between Awareness of Agentic AI (AA), Perceived Anticipatory Capability (PAC), Perceived Risk Reduction (PRR), Trust in Agentic AI (TAI), Behavioral Intention to Adopt (BI), and Investment Decision Confidence (IDC). Findings reveal that PAC significantly mediates the relationship between AI awareness and investor trust, and that trust is the most powerful predictor of adoption intention. Furthermore, IDC is confirmed as a downstream outcome of adoption readiness. The paper contributes a theoretically grounded, empirically validated framework for deploying Agentic AI in volatile stock environments and offers practical implications for fintech developers, SEBI regulators, and investor education programmes.
Keywords Keywords: Agentic AI, power sector stocks, pre-emptive risk detection, structural equation modelling, investor behaviour, Impact of fintech in India.
Field Business Administration
Published In Volume 17, Issue 7, July 2026
Published On 2026-07-17
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