Can AI help retail investors make consistent money in trading? Here's what Nithin Kamath says

Nithin Kamath has poured cold water on the growing belief that artificial intelligence (AI) can help retail investors consistently make money in the stock market, arguing that both human psychology and structural realities limit any such advantage.

In a post on X, Kamath said that despite rapid advancements in AI tools, trading outcomes are still largely shaped by human behaviour. As long as investors remain involved in decision-making, fear and greed continue to drive actions, leading to repeated mistakes such as panic selling and impulsive trades.

Beyond behavioural biases, Kamath pointed to a more fundamental constraint, the absence of a sustainable informational edge in modern markets. He argued that most publicly available information is quickly priced in, making it difficult for individual traders to consistently outperform. Even in cases where inefficiencies exist, assuming that markets are efficient remains a safer operating principle.


"Participants who do generate steady profits are not retail traders using tools, but institutional players such as high-frequency trading firms, market makers and proprietary desks," he said, adding that these entities operate with significant advantages built over years, including low-latency infrastructure, access to high-quality data and large capital commitments.

Kamath's remarks come at a time when AI-driven trading tools, signals and automation platforms are gaining popularity among retail investors, often marketed as a way to improve returns or identify opportunities faster than traditional methods.

However, he drew a clear distinction between using AI as a profit-generating engine and using it as a behavioural tool. In Kamath's view, AI's real utility lies in helping traders execute strategies with discipline rather than enhancing their ability to generate alpha.

"What AI can do is help you build and test strategies, then execute them systematically, removing emotion from the equation. That means fewer panic sells, less revenge trading and more consistency. What it can't do is turn a bad strategy into a good one or create a magic money tree."

That said, Kamath cautioned that technology cannot compensate for flawed thinking. A weak or poorly designed strategy will not become profitable simply through automation or AI support. In other words, AI cannot create an edge where none exists.

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