Artificial intelligence (AI) tools are increasingly popular among investors for research and analysis. However, experts caution against handing over key investment decisions to AI systems. While AI can assist in gathering data and offering insights, human judgment remains essential to avoid costly errors.
Bob Lai, a personal finance blogger, uses AI platforms like ChatGPT, Gemini, and Claude to support his investment research, especially with dividend-paying stocks and index ETFs. He relies on AI to analyze stocks and identify gaps in his research but always retains final decision-making control. "I want to make sure a human (i.e. me) is behind the final decision-making process," Lai emphasizes.
AI’s Role Is Support, Not Substitute
According to a 2025 Canadian Investor Study by Broadridge Financial Solutions, 88% of investors are likely to act on AI-generated information. Usage varies across generations, with millennials and Gen Z leading adoption. Yet, the risk lies in over-reliance without understanding AI's limitations.
Jason Pereira, a senior partner and financial planner, points out a common issue: many investors don’t know how to craft detailed prompts that capture the full context needed for AI to provide useful answers. For instance, a vague question like “What’s the best option to reduce my tax bill with $5,000 to invest?” misses critical details such as tax bracket, risk tolerance, and income. Without these, AI-generated advice can be misleading.
Lai agrees that detailed follow-up questions improve AI’s usefulness. He directs AI tools to review specific company financials, such as quarterly and annual reports over several years, to get more accurate insights.
“A Really Smart, Lazy Intern”
Pereira likens AI to “a really smart lazy intern.” It can deliver quick answers but often cuts corners or leaves tasks unfinished. Complex requests increase the chance AI will stop prematurely without flagging incomplete work.
For newcomers to both investing and AI, this creates a challenge. They face “unknown unknowns” — mistakes or gaps they aren’t aware of — making it difficult to judge the accuracy of AI’s responses. The perceived authority of AI may cause users to trust answers without verification, which can be risky.
Data Quality and Privacy Concerns
Lai also questions how AI tools gather and verify data. To mitigate risks, he instructs AI to focus on reliable sources during research. Privacy is another concern; Lai limits sharing personal data with AI and always does his own research first to form an independent opinion.
Beware of Confirmation Bias
Investors sometimes resist advice that challenges their beliefs, whether it’s from human advisors or AI. Pereira warns that investors can manipulate AI by rephrasing questions to get answers that confirm existing biases.
For example, requesting stock picks based on a preferred strategy may yield responses aligned with that strategy—even if it’s suboptimal. A better approach is to ask whether the strategy is sound based on empirical evidence and historical performance.
Key Takeaways for Finance Professionals
- Use AI tools as a research assistant, not a decision-maker.
- Craft detailed, context-rich prompts to improve AI output.
- Always verify AI-generated information using trusted sources.
- Be mindful of data privacy when using AI platforms.
- Watch out for confirmation bias when interpreting AI advice.
Incorporating AI into investment workflows can increase efficiency, but maintaining human oversight is critical. For professionals interested in improving their AI skills, exploring specialized courses in prompt engineering and AI tools for finance could be valuable. Resources such as Complete AI Training’s finance-specific AI tools offer practical guidance on effective AI use.
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