But AI-generated financial information is not the same as personalised financial advice.
Investors need to understand what the technology can do, what information it is using and who remains responsible for a recommendation before acting on it.
What can AI do for an investor?
AI can process large amounts of information much faster than a human. This can include company filings, earnings calls, research reports, market data and portfolio information.
Apurv Gupta, Founder and CEO, Otto Money, an AI-powered wealth management and financial guidance platform, said AI could eventually move beyond research to assessing an investor’s financial circumstances, including their balance sheet, risk appetite, human capital and aspirations, to determine what types of assets may fit their needs.
Rohit Agarwal, Co-Founder and CEO, and Fal Ghancha, Co-Founder and CTO, 72 Street, an emerging Indian fintech and wealth management startup, said AI could also connect different parts of an investor’s journey, including research, execution, portfolio tracking and learning, instead of treating them as separate activities.
This means an AI system could potentially help answer questions such as why a stock moved, how an investment fits into an existing portfolio or what could happen to a portfolio under different market scenarios.
Faster information does not mean better investment decisions
One of the key distinctions investors need to understand is between speed and decision quality.
AI can make research and analysis faster, but faster access to information can also encourage investors to act without adequately assessing risk.
Hemant Sood, Founder and Managing Director, Findoc Group, an Indian financial services conglomerate offering stock broking, investing, and wealth management services, said AI should help investors understand issues such as concentration risk, investment costs and potential drawdowns rather than simply make transactions faster.
Ramakant Yadav, Co-Founder, Scalar Field, an AI-powered, agentic trading desk and research platform, similarly said AI systems should be capable of showing why a recommendation was generated and should be designed to pause when they are uncertain rather than provide an unsupported answer.
Why does personalisation matter?
The same investment may not be suitable for every investor. A person’s income, existing assets, liabilities, investment horizon, liquidity requirements, risk tolerance and financial goals can all affect suitability.
This is where AI could potentially move beyond generic financial information.
Instead of simply answering whether a particular stock or fund looks attractive, a more personalised system could consider whether that investment fits the investor’s existing portfolio and financial objectives.
Gupta said the larger opportunity was to move from AI as a research tool towards a system that can provide more contextualised financial guidance.
However, personalisation also means that the quality and security of the information supplied to the system become important.
What should investors check before trusting an AI recommendation?
According to experts, investors should look at four broad areas.
First, understand the basis of the recommendation. Gupta said explainability would be important because investors may not trust a system that operates as a black box.
Second, check for conflicts of interest. Investors should know whether the platform has any commercial incentive linked to the products or investments it recommends.
Third, understand accountability. If AI is being used to provide actionable financial guidance, investors should know which regulated entity is responsible for that advice and how the recommendation can be reviewed.
Fourth, look at data security. A spokesperson from Fincart, an Indian online financial planning and wealth management platform, said platforms using AI in wealth management would need safeguards around client information, including appropriate data-security and privacy controls.
Can AI replace a financial adviser?
Experts see the role of advisers changing rather than disappearing immediately.
The Fincart spokesperson said activities such as research, analysis, portfolio construction, monitoring, reporting and scenario planning could increasingly be automated. Human advisers could consequently spend more time on judgement, behavioural coaching and helping clients deal with emotional decisions.
Sood also highlighted the behavioural aspect of investing. AI can identify patterns and flag risks, but investors can still react emotionally during sharp market movements.
This is important because investment outcomes depend not only on selecting an asset but also on how an investor behaves during periods of volatility.
What is responsible AI in investing?
Responsible use of AI requires more than simply connecting an investment platform to a generative-AI model.
Gupta said financial AI systems need to be grounded in reliable data and should clearly distinguish between generic information and actionable guidance. Actionable recommendations, he said, should be capable of being audit-logged and reconstructed.
The 72 Street founders said responsible adoption should include validation of AI outputs, data governance, auditability and human accountability.
Yadav said platforms should also maintain records of AI-driven decisions so that a recommendation can be reviewed later and the reasoning behind it understood.
What could AI change for retail investors?
Arindam Ghosh, Head – India & South Asia, IMA, a global professional association for accountants and financial professionals in business, said AI could make personalised financial insights and planning tools more accessible, including to people in smaller cities and those more comfortable using regional languages.
The potential benefit, therefore, is not simply faster stock research. AI could make financial information and certain forms of personalised guidance available to a much larger investor base.
But access to technology does not remove the need for financial judgement. Ghosh said investors would still need to understand risks, question recommendations and make responsible decisions.