Madam Dear Leads Liberator in Exploring the Future of Investing, Asking “Can AI Really Invest 100% on Our Behalf?” at Techsauce Global Summit 2026

As AI continues to transform both the business landscape and investor behavior, the question of whether AI can invest on our behalf 100% took center stage at Techsauce Global Summit 2026. The discussion invited audiences to look beyond the use of AI merely as a tool for searching and summarizing information, and instead consider how ready the technology is to play a meaningful role in actual investment decision-making and portfolio management.

Watanya Bunnag, or “Madam Dear,” Co-CEO of Liberator Securities, shared her view that the key challenge in bringing AI into the investment world is not simply about making technology as “intelligent” as possible. Rather, it is about enabling technology to help investors gain easier access to information, investment tools, and high-quality decision-making processes.

Today, AI is increasingly capable of supporting data processing, monitoring market developments, analyzing assets, and assisting with risk management. However, certain decisions cannot be handed over entirely to technology, particularly an individual investor’s risk tolerance, financial goals, investment horizon, and personal life plans.

Therefore, the concept of “letting AI invest 100%” does not mean giving AI complete autonomy to make every decision on behalf of humans. Instead, it refers to using technology to systematically carry out the investment process within clearly defined risk parameters and conditions set by the investor.

This concept also reflects Liberator’s direction and belief that high-quality investment tools should not be limited to large investors or those with access to premium financial services. Technology should instead be used to reduce those barriers and make effective investment tools more accessible to a broader group of investors, in line with Liberator’s philosophy of “Investment for Everyone.”

LLMs Help Investors “Understand Information,” While Quantitative Systems Help “Measure and Make Decisions Systematically”

Thanin Sammanee of Deepscope expanded on the technical perspective by explaining the different roles of Large Language Models (LLMs) — AI systems capable of reading and understanding human language — and quantitative analysis and rules-based investment systems, both of which are becoming increasingly important technologies in the investment landscape.

LLMs are particularly effective at reading, understanding, and connecting large amounts of information presented in natural language. They can help investors search for information, read and summarize news, analyze financial statements, and understand key developments surrounding a company more quickly.

However, using outputs from an LLM directly as investment decisions still comes with limitations, particularly the risk of hallucination, where the system may generate inaccurate or misleading information, as well as concerns regarding the quality and sources of the data being processed.

By contrast, quantitative analysis and rules-based investment systems bring data into a structured measurement and comparison process using consistent criteria. These may include earnings growth, share prices relative to fair value, price trends, and risk levels. The information is then transformed through a systematic process of:

Data → Score → Signal → Decision

This helps make both analysis and decision-making more systematic.

The key point, therefore, is not to determine whether LLMs or quantitative analysis systems are superior, as the two technologies perform different functions. LLMs help investors read and understand information more quickly, while quantitative systems help measure, compare, and convert that information into signals for decision-making.

The development of AI for investing should therefore not rely on any single technology alone. Instead, AI capabilities need to be connected with high-quality data and clearly defined analytical systems, allowing investment decisions to be better grounded, explainable, and verifiable.

Having More Information Does Not Necessarily Lead to Better Investment Decisions If Emotions Still Take Over

From an investor’s perspective, Metapon Amorntirasan, founder of the investment page Hoonpleanlok, noted that another major challenge in investing is not necessarily a lack of information, but the ability to maintain “investment discipline.”

Even when investors have conducted thorough research, have sound reasons for making an investment, and have established a long-term plan, short-term market volatility or sudden news flows can still allow fear and greed to influence their judgment and cause them to deviate from their original strategy.

In an era where AI can generate and summarize vast amounts of information at remarkable speed, having more information does not automatically lead to better investment decisions if investors are unable to assess the quality of that information or manage their own emotions.

The most valuable role of AI for investors in the future may therefore extend beyond simply answering questions such as “What should I buy?” or “When should I sell?” Instead, AI should be able to help investors organize information, establish a systematic decision-making process, and maintain discipline within the investment framework they have set for themselves.

From an AI Assistant to a Tool That Supports the “Investment Process”

Looking at the broader picture across the perspectives of technology providers, investors, and investment service providers, the key question is no longer simply whether AI will become capable enough to invest on behalf of humans. Rather, the more important question is how AI should be designed to work appropriately alongside humans.

For Liberator, this direction means developing AI beyond the role of a simple question-and-answer tool or information-search assistant. The company places particular importance on ensuring that AI operates with accurate and high-quality data, structured databases, and clearly defined analytical processes, so that the technology can provide more meaningful and practical support throughout the investment process.

Liberator is currently preparing to further develop this concept into new AI-powered investment services, with the aim of creating tools that can help investors manage information, analyze and monitor investments, and manage their portfolios more systematically within risk parameters appropriate to each individual.

The goal is not to develop AI in order to eliminate the role of humans in investing. Instead, Liberator aims to use technology to reduce the complexity of the investment process and enable more people to access high-quality investment tools — without making the size of an investor’s portfolio a prerequisite for access.

This represents another step forward for Liberator in advancing its “Investment for Everyone” philosophy, making technology, data, and sophisticated investment tools that were once difficult to access more widely available and practical for a broader range of investors.

Ultimately, the question of whether “we would dare to let AI invest 100% on our behalf” may not be answered by whether AI can accurately predict the market every time. Instead, it depends on how well the system understands the owner of the money, whether it can keep risk within predefined boundaries, and how clearly it can explain the reasoning behind its decisions.

A trustworthy investment technology does not necessarily need to make every decision on behalf of humans. What matters is its ability to help people make decisions and manage their own money in a more structured and systematic way.