Techsauce Global Summit 2026: Can AI Invest For Us 100%
Key insights from 3 experts at Techsauce 2026 on AI investment roles, limitations, and why humans should still manage the core strategy.
Stock photo for illustration only, not from the actual event
- AI assists with data processing and market tracking, but 4 personal areas require human control.
- LLMs excel at summarizing news but risk inaccuracies, while Quant systems are rule-based and objective.
- The biggest investment barrier is lack of discipline during volatility, not a lack of information.
- Experts advise using AI as an assistant and testing with a fraction of capital rather than full automation.
Artificial intelligence is playing an increasingly vital role in the investment world, ranging from data gathering and news summarization to business analysis and stock screening. This progress sparks a critical question: if AI takes on more of the investment process, would we dare let it manage our money entirely?
This topic was discussed in the session 'Would You Dare to Let AI Invest for You 100?' at the Techsauce Global Summit 2026, featuring Watanya Bunnag, Co-CEO of Liberator Securities; Thanin Sammanee, CEO and founder of Deepscope; and Methapon Amorntheerasarn, an investor and owner of the Stock That Changes the World page.
Watanya Bunnag noted that the core of applying AI to investing is enabling investors to access quality data, practical tools, and make better decisions. Although AI currently helps process data, track markets, and monitor risks, she emphasized four areas that AI should never decide on behalf of the owner: risk tolerance, financial goals, investment timeline, and life plans, as these are entirely personal matters.
Stock photo for illustration only, not from the actual event
From a technological standpoint, Thanin Sammanee explained that we must distinguish between Large Language Models (LLMs) and numerical analysis systems. LLMs are exceptional at processing text, summarizing news, and reading financial statements quickly, though they carry the risk of hallucinations or unverified sources. Conversely, Quant systems operate on strict rules and formulas, evaluating indicators consistently, and can now utilize Machine Learning to generate stock-screening formulas independently.
"The biggest barrier in investing is not a lack of information, but a lack of discipline."
Methapon Amorntheerasarn
Methapon Amorntheerasarn added that having an abundance of data does not guarantee better decisions if investors lack discipline against fear and greed during market volatility. While AI is evolving into an AI Agent or a 'second brain' that thinks analytically, he believes AI should not manage all funds because LLMs tend to over-weight recent news trends. Investors should test systems with only a portion of their capital rather than committing entirely.
Further analysis highlights that integrating AI into investment represents a crucial transitional phase between automating away human emotional bias and mitigating technical risks such as data inaccuracies or short-term news over-weighting. Combining human understanding of life goals with precise algorithmic calculation remains the most balanced approach today.
Looking ahead, Watanya Bunnag revealed that Liberator is preparing to launch a new AI service designed to help investors manage data, analyze markets, and handle portfolios systematically within acceptable risk parameters, aiming to reduce complexity and broaden access to high-quality tools for all investors.
Source: Techsauce
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