Artificial intelligence has moved from being a novelty to a necessity in everyday life. We use it to write, edit, search, and create. It helps us save time, reduce effort, and make quicker decisions.
Gradually, it has become a tool we depend on without thinking twice. Now, that same technology is being trusted with something far bigger; our money.
People have started relying on AI to make decisions, whether it is picking a stock, understanding market trends, or figuring out when to buy and sell?
At recent app launches and updates across India’s fast-growing fintech space, one thing has become clear. Artificial intelligence is no longer just a feature inside financial apps, it is the main pitch.
From stock suggestions and portfolio insights to some tools that claim to help users “time the market”, AI is increasingly being positioned as a smarter way to invest.
But when money is involved, the question becomes far more important than the technology itself, how much should you actually trust it?
The use of AI in financial services is not new, but its role is expanding rapidly.
According to Sebi’s consultation paper on responsible usage of AI and machine learning, these systems are already being widely used across Indian securities markets — from advisory and support services to surveillance, risk management, and even product recommendations.
Better data, faster computing power, and advances in generative AI have pushed this adoption further.
For platforms, the logic is simple. Markets move fast. Data is overwhelming. And retail investors need help navigating both.
“AI helps us process large volumes of data quickly, identify patterns, and present information in a more usable way,” said Navy Vijay Ramavat, Managing Director at Indira Securities.
“It strengthens decision-making by reducing noise and improving efficiency.”
For users, AI promises something very appealing, better decisions with less effort.
Instead of tracking earnings reports, analysing charts, or reading research reports, investors can now rely on AI-powered tools to simplify the process.
But even companies building these tools are careful about how far they take that promise.
“AI does not replace that team, it amplifies what they can do,” said Pranit Arora, Co-Founder and CEO of Univest.
“Every investment recommendation that reaches our users originates from a qualified, human research team.”
He added that AI is used to speed up analysis and filter information, but not to make final decisions.
“AI at Univest is an analytical co-pilot, not an autonomous decision-maker.”
One of the boldest claims being made today is that AI can help investors “time the market”.
But this is where experts draw a clear line.
“I want to be very direct here: we do not claim to ‘time the market’,” Arora said.
“Market timing is something even the most sophisticated institutional funds struggle with.”
Navy Vijay echoed a similar view.
“Timing the market perfectly is a myth. No one can do it consistently,” he said.
What AI can do, according to both experts, is identify patterns and highlight possible opportunities — not predict exact outcomes.
Despite the hype, the reality is more measured.
At Univest, AI is used to:
screen large sets of stocks
analyse data across parameters
generate internal “conviction scores”
But the final call still rests with human analysts.
At Indira Securities, the approach is even more conservative.
“AI on our platform works as an assistive layer to simplify complex market information, not as a recommendation engine,” Vijay said.
In many cases, core tools are not AI-driven at all.
Instead, AI is used for:
summarising market updates, organising data, and simplifying insights
Even as platforms highlight the benefits, they also acknowledge limitations.
At Univest, Arora said the firm tracks performance closely.
“Our advisory track record shows an approximately 86% accuracy rate,” he said. That also means a portion of calls do not work out.
“The 14% of calls that do not hit the target are equally important,” he added.
At Indira Securities, the approach is less about accuracy and more about context. “In markets, accuracy is never absolute,” Vijay said.
This highlights a key point, AI can improve decision-making, but it cannot eliminate risk.
One of the biggest concerns around AI in investing is not the technology itself, but how people use it.
When recommendations become simple and easy to follow, there is a risk that users stop questioning them.
This is exactly the kind of risk Sebi has flagged.
The regulator has warned that AI systems can create or amplify risks that may impact market efficiency and investor outcomes.
These include:
Another concern is that AI systems are not always accurate. “We approach this very carefully,” Vijay said.
“AI systems can make mistakes, especially while reading complex or poorly formatted documents.”
To manage this, some platforms provide users with the original data alongside AI-generated summaries.
This allows users to cross-check information before acting on it.
Recognising these risks, Sebi has laid out clear guidelines for how AI should be used in financial markets.
These include:
In simple terms, AI cannot operate without checks.
This is where things become complicated.
If an investor follows an AI-driven suggestion and loses money, who is responsible?
The answer, for now, is not straightforward.
“Under Sebi guidelines, a registered research analyst provides recommendations, not guaranteed outcomes,” Arora said.
Most platforms position AI as a support tool, not a decision-maker.
“We clearly position all insights as inputs to support decision-making, not as instructions,” Vijay said.
This means the final responsibility still lies with the user.
Across both experts, one message is consistent.
AI is useful. But it is not meant to replace human judgement.
“AI proposes; humans approve,” Arora said.
The role of AI, as they describe it, is to process data faster, highlight patterns, and simplify information.
But the final decision still needs to come from the investor.
AI is clearly reshaping how people interact with financial markets.
It is making investing faster, more accessible, and more data-driven
But it is also introducing a new layer of complexity, one where decisions are increasingly influenced by systems users may not fully understand.
AI can help you invest better. It can make information easier to understand and decisions easier to take.
But it cannot remove uncertainty.
And it cannot take responsibility for your money.
(Disclaimer: The views, opinions, recommendations, and suggestions expressed by experts/brokerages in this article are their own and do not reflect the views of the India Today Group. It is advisable to consult a qualified broker or financial advisor before making any actual investment or trading choices.)