Wall Street professionals are finding practical applications for AI chatbots, despite acknowledging the technology’s limitations in replacing core financial work. While industry experts express caution about relying on AI for fiduciary responsibilities and sophisticated analysis, they’ve discovered creative ways to leverage tools like ChatGPT, Claude, Perplexity, and Copilot for time-saving tasks.
Maurits Pot, founder of Tema ETFs, emphasized the risks of using chatbots for client-facing work, while David Trainer of New Constructs highlighted concerns about AI hallucinations making the technology unreliable for precise financial data. Despite these limitations, adoption is growing across the industry.
One of the most innovative applications comes from Lance Roberts, CIO at RIA Advisors (managing approximately $2 billion), whose team programmed 14 different AI agents to emulate legendary investors including Warren Buffett, Stanley Druckenmiller, Benjamin Graham, John Bogle, and Cathie Wood. These virtual advisors provide diverse perspectives on market views and individual stock analysis, helping teams consider multiple investment angles.
Rob Arnott, founder of Research Affiliates, uses AI for book summarization and research feedback. He had ChatGPT summarize Sun Tzu’s “The Art of War” for his team to prepare for Trump’s second term, saving valuable time while ensuring key takeaways were captured. Arnott favors Perplexity as his primary search engine, describing it as “an AI of AIs” that selects the most appropriate AI model for each query. He also uses AI for detailed feedback on his research papers.
Administrative tasks represent the most common use case, with Seth Klarman, CEO of Baupost Group, comparing AI to “essentially a capable assistant, a summer intern.” David Elder of Merit Financial Advisors uses multiple chatbots (ChatGPT, Copilot, and Gamma) to convert recorded interviews into presentations, significantly streamlining his workflow.
Chase Doyen from London Stock Exchange Group relies on Claude (Anthropic’s chatbot) primarily for organizational purposes, including planning his day and cleaning up meeting notes. The consensus among Wall Street professionals suggests AI excels at supporting tasks rather than replacing sophisticated financial analysis.
Key Quotes
If you’re doing it for self-education, it’s one thing, but I think it’s quite hard to rely on a chatbot for fiduciary purposes if you’re facing clients
Maurits Pot, founder of Tema ETFs, explains the fundamental limitation of AI in finance—the inability to trust chatbots with fiduciary responsibilities where client money and trust are at stake.
You don’t use AI to do sophisticated things. It’s more trouble for me to use something and find out later that it’s hallucinated than it is for me to just go get it from the source to begin with
David Trainer, founder of New Constructs, articulates why AI hallucinations make the technology unsuitable for complex financial analysis where precision is critical.
Perplexity is my preferred search engine, and has been for a couple of years now. The nice thing about Perplexity is that it’s an AI of AIs: it chooses which AI is best suited to whatever question I have
Rob Arnott, the renowned investor and founder of Research Affiliates, explains why he favors Perplexity over other AI tools for research and feedback on his papers.
essentially a capable assistant, a summer intern
Seth Klarman, CEO of Baupost Group, succinctly captures how Wall Street views AI’s current capabilities—useful for support tasks but not ready for sophisticated financial work.
Our Take
Wall Street’s measured AI adoption offers a reality check against Silicon Valley’s transformative promises. The most telling insight is that sophisticated investors who analyze technology trends for a living remain skeptical of AI’s core capabilities in their own domain. The creative workaround of programming AI agents to emulate legendary investors is both innovative and revealing—it suggests professionals want diverse perspectives but don’t trust AI’s independent judgment. The emphasis on administrative applications validates concerns about AI’s impact on entry-level positions, potentially eliminating traditional pathways into finance. However, the persistent reliability issues suggest we’re still in early innings. What’s particularly noteworthy is that even enthusiastic adopters frame AI as augmentation rather than replacement, indicating that human expertise remains the competitive advantage. This pragmatic approach from an industry that moves billions daily should inform expectations across other sectors.
Why This Matters
This article reveals the pragmatic reality of AI adoption in finance, one of the world’s most data-intensive and high-stakes industries. While AI hype suggests revolutionary transformation, Wall Street’s cautious approach highlights the technology’s current limitations in mission-critical applications where accuracy and fiduciary responsibility are paramount.
The creative applications—particularly programming AI agents to think like legendary investors—demonstrate how financial professionals are finding value in AI as a collaborative tool rather than a replacement for human expertise. This pattern likely reflects broader trends across knowledge-work industries: AI augments rather than replaces skilled professionals.
The emphasis on administrative tasks and “summer intern” level work suggests AI’s immediate impact will be on entry-level positions and support roles, potentially reshaping career pathways in finance. However, the persistent concerns about hallucinations and reliability indicate that human oversight remains essential, especially in regulated industries. This measured adoption approach by sophisticated financial professionals provides a realistic benchmark for other industries evaluating AI integration, suggesting the transformation will be gradual rather than disruptive.
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Source: https://www.businessinsider.com/wall-street-top-ai-chatbots-tools-claude-chatgpt-gamma-2026-1