AI Adoption for Indian Stock Trader

AI Adoption for Indian Stock Trader

Gajendra Singh (MBA) Lovely Professional University.

Sonu Sagar (MBA) Lovely Professional University.

Bhawesh Gupta (MBA) Lovely Professional University

Abstract
The introduction of Artificial Intelligence in the stockbroking industry is changing the Indian financial landscape, making it more efficient and leading to much more informed decision-making. This paper explores how Indian stockbrokers how Indian stock brokers are utilizing AI for stock recommendations to an individual. are utilizing AI to impact SIPs and investment in mutual funds. SIP contributions have crossed ₹2.5 lakh crore per year by 2024, which shows growth in participation by investors. With more than 10 crore Demat accounts and capacities ranging from a novice to the most seasoned trader, a case can be built for AI-driven tools that addresses diverse financial literacy.

A critical distinction is drawn between trading, income generating, and involving scalp, intraday, and swing techniques, and investing, which is wealth building with a focus on the short-term and long horizons. These require appropriate AI applications to achieve best outcomes with minimum risks. As per today there are different kind of assets like equity, forex, commodity, Bullion, crypto, government securities, cooperate bonds, fixed deposit available to an individual trader. —whether appreciating like equities and mutual funds or depreciating like vehicles and gadgets—is an impact on investment decisions, making AI provide them best recommendation based on their risk appetite how much and how long an individual trader has to invest in same or a bunch of available assets and that helps him to build a high profitable portfolio.AI provide them best recommendation based on their risk appetite how much and how long an individual trader has to invest in same or a bunch of available assets. And build a high profitable portfolio. relevant in the process of asset selection and portfolio management.

The paper applies the diffusion of innovation framework for the assessment of AI adoption by Indian stockbrokers. Use of a line graph depicts the journey from the earliest to the widespread adoption stages. Predictive analytics, sentiment analysis, and personalization- three capabilities that have become priceless to modern financial ecosystems, are the main enablers of the phenomenon.

This research highlights how AI is not just a tool but a transforming force for Indian stockbrokers by humanizing AI applications and discussing the issues of trust, accessibility, and adaptability. Findings are aimed at filling in knowledge gaps, empowering investors, and opening the door to sustainable financial growth in India.

Keywords: Artificial Intelligence, stockbroking, Indian financial landscape, decision-making, stock recommendations, SIP contributions, Demat accounts, AI-driven tools, trading techniques, investment