How to Use AI for Smarter Investing in India 2025

Artificial Intelligence (AI) is rapidly changing the world of investment in India. By 2025, spending on AI in India is estimated to reach around ₹ 14,300 crore, showing a growth of more than 31% year-on-year (IDC report). At the same time, individual investors are now also using data analytics and machine learning to better understand market trends.

In this blog, we will explain to you in simple language how you can make your investments even smarter, faster and more accurate by using AI. 

AI in Investing

AI (Artificial Intelligence) means programming machines with the ability to think and make decisions like humans. ML (Machine Learning), a subset of AI, learns from data provided. Deep Learning is an advanced form of ML that uses artificial neural networks and tries to work a little like our brains.

1). How is AI different from traditional tools?

• Earlier, screeners and algorithms picked stocks based only on predefined financial rules (such as the P/E ratio).
• But now, AI-powered tools understand sentiment, scan news, technical and fundamental data in real-time, and create strategies on their own and moreover, they can also identify market patterns. This reduces the scope of human error and emotional decisions.

2). AI: Real-World Applications

• Robo-advisors: These are AI-based advisors that understand your risk appetite, goals, and financial habits and guide you in investing. 
• Sentiment Analysis: AI analyzes investor sentiment from Twitter, news, Reddit—for example, when the Adani-Hindenburg controversy happened, AI-based sentiment tools were able to detect sentiment changes and predict price fluctuations quickly.
• Portfolio Optimization: AI can easily balance portfolios, manage risks, and detect frauds with ML and predictive analytics.

Read Also: Best Artificial Intelligence (AI) Stocks In India

How AI Affects the Investment Process?

Today’s investor is not limited to just charts and ratios. AI is now playing a broader role making decision-making at every stage faster, personalized, and more data-driven. Let us evaluate the role of AI in the investment process based on different metrics mentioned below:

1). How is AI changing the Research Process?

The traditional research process was time-consuming and subject to personal bias. AI is making this process automatic, neutral, and much more in-depth. Many of today’s AI tools can scan everything from financial documents to CEO statements.

For example, NLP-based systems can analyze management discussion and analysis (MD&A) sections in the annual reports and guess whether their tone is bullish or bearish.

2) How does AI make Portfolio Management easier?

Every investor’s financial goal, risk-taking capacity, and holding period are different. AI can create tailored portfolios based on investor’s individual preferences.

• Through data analytics, AI decides how much should be invested in which asset class — equity, debt, gold or international funds.
• Mutual Fund houses like Nippon India are now integrating AI into their smart asset allocators, which reallocate portfolios as per market changes.
• Also, smart-beta ETFs and factor-based investment plans are growing rapidly in India, which are based on indicators such as volatility, quality, and momentum selected by AI.

3). How is AI making Risk Management more accurate?

Financial frauds, extreme volatility, and behavioral biases all of these can impact an investor’s portfolio. AI provides real-time solutions to all of these.

• Many SEBI-registered fintech platforms in India are now using AI to track transaction patterns and report any unusual behaviour immediately.
• In the banking sector, credit card companies are now using AI-based behavioral scoring to assess a person’s repayment capacity taking into account real-time spending behavior, not just income or CIBIL score.
• NBFCs and digital lending apps are also now using neural networks and decision trees instead of traditional ratio models for risk estimation.

4). How does AI read News and Market Sentiment?

Markets today are not just driven by numbers; emotions, Twitter trends, media coverage and global events also influence investment decisions.

• Sentiment analysis tools like FinBERT can now analyze social media and news data to determine public sentiment about a company or sector.
• These tools not only provide scores, but also suggest which sectors are seeing a sudden surge in interest or a decline.
• For example, when the report concerning the Adani Group was published in 2023, many sentiment trackers had already indicated a negative trend, allowing proactive decisions to be taken.

Read Also: Scope of AI in Investing: Usage, Benefits, and Challenges

AI Based Investment Platforms in India

Let us look at the AI based investment platforms that are popular in India:

• Smallcase : Smallcase is a unique platform where you can invest directly in stock portfolios created by InvestorAi, Wright Research, etc. These smallcase fund managers create investment portfolios based on suggestions from AI-powered robo-advisors scanning real market data. 
• Jarvis Invest : Jarvis is an advanced robo-advisory platform that suggests smart stock recommendations based on your risk profile, age, and financial goals. The platform dynamically manages the portfolio by processing real-time data.
• ET Money Genius : ET Money Genius is a new AI-powered feature that suggests a customized portfolio strategy based on the user’s financial goals and risk profile. It offers weekly rebalancing, downside protection and smart asset allocation.

Read Also: 5 Top Artificial Intelligence Penny Stocks in India

Limitations, risks and ethical concerns in AI investments

Some of the risks, limitations and ethical concerns regarding use of AI in making investments is given below:

• Incomplete and Biased Data : AI models are often trained on historical data. If this data is biased or incomplete, the model may incorrectly predict future trends. This can lead to wrong investment decisions, increasing the likelihood of losses.

• False Signals due to Noise : There is a lot of noise in short-term price movements in the stock market. Sometimes AI interprets this noise as a meaningful signal, which can lead to incorrect buy/sell suggestions especially in high-frequency trading.
• Blind Reliance Without Human Judgment : AI-based tools are powerful, but relying on them blindly can be dangerous. AI cannot understand financial statements, news context or geopolitical events as well as humans do currently. Therefore, the investor should also do some analysis and check AI recommendations before investing.
• Lack of Regulatory Clarity (in India) : SEBI has not yet fully implemented any dedicated framework governing AI trading or robo-advisory. 
• Ethical Concerns: Users often do not understand how AI algorithms work. If a wrong decision is made, the resulting trades can contribute to market volatility or unintended price movements.
• Data Privacy & Cybersecurity Risks : AI platforms get sensitive information from users such as financial data, income information and investment habits. If this data is not encrypted or protected properly, hackers can misuse it. Apart from this, investor accounts may also be at risk of cyber-attacks.

Read Also: What is AI Washing? Definition, Tips, Evolutions & Impact

The Future of AI in Indian Stock Markets

Now let us evaluate the future of AI in Indian stock market:

• SEBI’s AI-ML Guidelines : In June 2025, SEBI released a consultation paper for AI/ML use, focusing on five key aspects: Model Governance, Mandatory Disclosure, Continuous Testing, Bias Control, and Data Security. These rules are a step towards making areas like investment advice, robo-advisory, algo-trading transparent, fair and secure.
• Opening the door for retail investors to algo trading : Another proposal from SEBI came in April 2025—in which there was a discussion on allowing retail investors to do algorithmic trading. Now, even retail investors can connect their AI based stock recommendation algos with their broker APIs and do algorithmic trading.
• SEBI implements AI Accountability for Regulated Intermediaries : The new SEBI regulations of February 2025 holds market infrastructure institutions and intermediaries (such as advisory firms, brokerages) accountable for any consequences arising from AI use—this includes responsibility for ensuring data security and outputs resulting from operations and client services. This means, if an AI model executing trade causes high volatility in stock prices, then the platform will be held responsible.
• RBI’s AI-Ethics and Security Framework (‘FREE-AI’) : In December 2024, RBI formed its ‘FREE-AI’ committee which will ensure ethical and responsible use of AI in the financial sector , This will also impact banking and payment platforms, creating a strong AI-governance ecosystem.

Read Also: Best Artificial Intelligence (AI) Smallcap Stocks

Conclusion 

AI is slowly becoming the most powerful ally of investors for various applications such as data analysis, personal financial planning, or forecasting trends. But with this growing influence of technology comes the need for prudence, regulation, and data security. As much as investors embrace AI, it is equally important to choose the right platform, understand data privacy, and avoid misconceptions. In the times to come, AI will not only make investing easier but also more responsible and secure. It is advised to consult a financial advisor before making any investment decision based on AI recommendations given by platforms.