Artificial intelligence has started finding its way into personal finance, quietly embedding itself in the way we manage money. From tracking shopping behaviour to forecasting the next likely expense, AI-based financial tools are rapidly gaining traction. Yet the big question remains: should you allow AI to take full charge of your financial decisions, or is it wiser to treat it as a supportive assistant that provides insights without overriding human judgment?
Experts like Sameer Mathur, MD, Founder of Roinet Solution, and Manish Mohta, Founder of Learning Spiral, suggest that while AI has enormous potential in simplifying money management, it should not be viewed as a substitute for personal decision-making. Instead, it is best positioned as an intelligent guide that highlights trends, savings opportunities, and spending risks while leaving the ultimate choice to the individual.
AI-driven spending platforms are designed to go far beyond a basic monthly expense report. They comb through vast amounts of transaction data and detect recurring trends, spikes, or habits that might otherwise go unnoticed. As Mathur explains, these systems are capable of processing immense financial data at lightning speed, identifying areas where costs can be trimmed, and even offering customized recommendations tailored to a user’s lifestyle. This helps people align their spending patterns with long-term goals like saving or investing. In practical terms, AI draws connections between small yet telling behaviours—such as frequent late-night food orders, festive shopping sprees, or habitual weekend purchases—and translates them into actionable insights.
Mohta likens AI to a bluntly honest friend who remembers all your impulsive spending habits, including those late-night splurges you may prefer to forget. By identifying patterns such as recency bias, overspending during certain seasons, or repeating purchases, AI acts as a mirror, offering clarity where human memory or selective perception may fail.
On the technical side, AI has proven to be impressively accurate in parsing financial records, often exceeding 90% accuracy when data is properly categorised and complete. These tools can even uncover overlooked transactions like a small subscription fee deducted monthly. Still, errors remain possible—cash purchases, shared expenses, or mislabelled entries can confuse algorithms, making occasional human checks indispensable.
A key area of concern, however, lies in data privacy. Since financial records are among the most sensitive categories of personal data, choosing the right platform becomes crucial. Trusted tools comply with regulatory frameworks such as RBI guidelines or Europe’s GDPR, ensuring bank-level security and clear privacy policies. Mathur stresses the importance of choosing services with transparent terms and strong encryption, while Mohta advises steering clear of providers with vague or confusing policies. He emphasizes that users should always have control, including the right to delete their data at will.
Despite its strengths, both experts caution against handing over complete financial control to AI. Mathur describes it as a supplementary aid, while Mohta compares it to a GPS system that warns of risks and highlights alternative routes but doesn’t decide the final destination. Ultimately, individuals must weigh their own goals, family responsibilities, and risk tolerance—factors that no algorithm can fully understand.
In conclusion, AI excels at breaking down numbers, finding patterns, and giving quick feedback, making it a powerful companion for anyone hoping to monitor and improve their spending. It can flag issues, suggest smarter approaches, and highlight hidden costs, but the final responsibility rests with the individual. When combined with human intuition and judgment, AI becomes less of a replacement and more of a reliable financial partner—helping people stay informed and make better choices without losing control over their own money.
