AI Investment Advice Gains Popularity in India
AI tools offer investment advice, but can they be trusted? Experts weigh in.

A growing number of retail Indian investors are seeking investment advice from AI-powered tools, with over 22.9 crore demat accounts in the country as of May 2026. Shubhodeep Pal, Chief Product Officer at SimpliFlying, has been using AI to analyze his investments, but he exercises caution and only approves trades proposed by the AI.
Pal's approach highlights the importance of human oversight in AI-driven investment decisions. While AI can process vast amounts of data and identify patterns, it can also be wrong and sound wise at the same time. Pal's rule is to only approve trades that have been thoroughly vetted, and he is skeptical of results that seem too good to be true.
A recent study by researchers from Massachusetts Institute of Technology and Stanford University found that AI's investment advice aligns closely with expert advice, but the outcome depends heavily on how the AI is queried. For example, women who used words related to everyday life in their questions were recommended lower-risk strategies with smaller stock allocations, resulting in lower average assets.
Rohit Prakash, Founder of Genvest, a SEBI-registered AI wealth management platform, notes that generic AI tools cannot provide meaningful guidance without understanding the user's financial profile and risks. Regulated AI platforms like Genvest analyze income, savings, portfolio, age, risk profile, and market conditions before recommending asset allocations.
The use of AI in investment advice is becoming increasingly popular, with many investors turning to generic tools like ChatGPT, Claude, and Gemini. However, experts warn that caution is necessary when relying on AI for investment decisions. AI tools can aid research, but financial advice is a personal matter that requires a deep understanding of the user's financial situation and goals.
As the number of demat accounts in India continues to grow, it is likely that more investors will turn to AI for investment advice. However, it is essential to remember that AI is not a replacement for human judgment and expertise. Investors should be cautious when using AI-powered tools and ensure that they understand the limitations and potential biases of these tools.
In conclusion, while AI can be a useful tool for investment research and analysis, it is crucial to approach AI-driven investment advice with caution and skepticism. Investors should always prioritize human oversight and expertise when making investment decisions, and regulated AI platforms may offer a more reliable and personalized approach to investment advice.
The growing popularity of AI investment advice in India highlights the need for greater awareness and education about the benefits and limitations of these tools. As the investment landscape continues to evolve, it is essential to prioritize transparency, accountability, and human oversight in AI-driven investment decisions.
The use of AI in investment advice is a rapidly evolving field, and it is likely that we will see significant developments in the coming years. As investors, it is essential to stay informed and adapt to these changes, while always prioritizing caution and skepticism when relying on AI for investment decisions.
In the end, the key to successful investment is a combination of human expertise, AI-driven analysis, and a deep understanding of the investor's financial situation and goals. By approaching AI investment advice with caution and skepticism, investors can make more informed decisions and achieve their long-term financial objectives.
Frequently asked questions
Can AI be trusted for investment advice?
While AI can provide useful insights, it is essential to approach AI-driven investment advice with caution and skepticism, and always prioritize human oversight and expertise.
What are the limitations of generic AI investment tools?
Generic AI tools cannot provide meaningful guidance without understanding the user's financial profile and risks, and may be subject to biases and limitations.