Can you trust AI over human intelligence to handle your stock portfolio?

AI has transformed stock trading by filtering and interpreting vast amounts of market news, company announcements, and sentiment indicators for active investors, delivering actionable insights without overwhelming users with data. This capability converts information overload into a strategic advantage for personal portfolios.

Kunal Nandwani, Founder and CEO of uTrade Solutions, says, “AI also enhances trading through automated complex strategies like long-short positions within user-defined parameters and improving portfolio management through advanced risk assessment techniques. These systems suggest optimal hedging strategies and asset allocations based on changing market conditions and investor goals, with precision impossible for human traders.

AI usage in stock trading

AI demonstrates significant value in analysing historical performance data and processing real-time market information. It excels at identifying patterns in existing data and monitoring live market movements. These capabilities make AI particularly effective for established trading patterns and known market behaviours.

However, AI shows clear limitations when projecting future performance of novel business models or predicting shifts in market patterns without historical precedent. AI trading systems may become actively detrimental during unprecedented market conditions like financial crises or geopolitical events, where historical data provides little guidance and human judgment becomes essential.

Limitations and risks

The primary limitations of AI-driven trading include potential misinterpretation of data and context, which is why AI-generated content should never be followed blindly. Additionally, AI systems may be vulnerable to manipulation by other AI systems or human act.

Another significant risk emerges when investors cannot properly understand or validate an AI's analysis methods, potentially exposing themselves to unexpected risks. This underscores the importance of maintaining strong, independent risk management systems that operate separately from AI trading tools to provide effective oversight.

Nandwani noted, “Companies offering AI-based trading advice face a fundamental challenge regarding accountability: who bears responsibility when AI provides incorrect advice, whether intentionally or unintentionally? This accountability gap creates regulatory complexities that current frameworks struggle to address, similar to challenges in regulating social media platforms that spread misinformation.”

“The regulatory landscape becomes particularly difficult because traditional compliance requirements designed for human advisors don't necessarily translate to AI systems,” he added. This creates potential blind spots that companies must navigate while the regulatory environment continues to evolve around the new technologies.

AI’s roadmap ahead

Experts believe AI will play a predominantly complementary role in investment advising rather than entirely replacing human advisors. Technology excels at data processing, pattern recognition, and consistent execution of established strategies, significantly enhancing human capabilities rather than rendering them obsolete.

“The most effective approach combines AI's analytical power with human judgment, emotional intelligence, and contextual understanding. This hybrid model leverages AI for its computational advantages while maintaining the human element essential for truly understanding goals, risk tolerance, and life circumstances in ways that technology alone cannot replicate,” said Nandwani.