Vietnamese
Why I Decided to Let AI Help with Investing
In over four decades of investing, I have done everything from long term buy and hold to value hunting and speculative bets. Some decisions paid off, enough to create million year gains over time. But with the rise of artificial intelligence in 2025, I started to wonder whether AI tools could genuinely improve my decision making. Could they save time, uncover hidden opportunities or at least offer a second opinion I trust?
That curiosity led me to try a concrete experiment. I opened a browser, used AI assistants and attempted to transform intuition and research into a more systematic process. The result was a real purchase, a real position and a firsthand experience of combining human judgment with machine power.
Below is the story of that journey. This is not investment advice, only a detailed case study showing how one investor used AI tools when searching for opportunities and how you might learn from the experience.
The Investment Thesis: AI and Biotech as a Downstream Play
My starting belief rests on a simple truth: artificial intelligence is not just a passing trend. It is reshaping entire industries. The companies designing and supplying the hardware, such as chipmakers and large tech groups building AI infrastructure, are obvious choices. I already own shares in many of them. But I wondered about the businesses further down the chain, the ones that use AI to enhance products, cut costs and support innovation.
One sector stood out: biotechnology. AI has the potential to accelerate drug discovery, speed up clinical trials, identify data patterns and support efficiency across research and development. These improvements could lead to breakthroughs, faster approvals and significant jumps in valuation for some biotech firms.
So my working thesis became: invest in small or mid cap biotech firms that could benefit from AI and become attractive takeover targets for major pharmaceutical companies.
It is a high risk, high potential thesis. But risk is part of investing. The important question was how to approach that risk intelligently, and that is where AI entered the picture.
Using AI as a Research Assistant: Conversations With ChatGPT and Copilot
Rather than diving directly into individual stocks, which carries enormous risk, I chose to begin with broader exposure, specifically an exchange traded fund focused on small and mid cap biotech.
First, I asked ChatGPT for a reality check on my thesis. I said:
I am thinking about investing in biotech stocks as a downstream AI play because I have read that medical breakthroughs will accelerate as AI becomes more powerful. Is that a good investment idea?
The response from ChatGPT was balanced. It agreed that AI is transforming drug discovery by supporting target identification, protein design and trial optimization, but reminded me that biotech firms are still highly risky with elevated failure rates and uncertain economics. The model suggested that using a diversified approach like an exchange traded fund was smarter than placing big bets on small pre revenue companies.
Next, I asked Microsoft Copilot which exchange traded funds focus on small and mid cap biotech firms with takeover potential. Copilot proposed several choices including the ALPS Medical Breakthroughs exchange traded fund, the Virtus LifeSci Biotech Clinical Trials exchange traded fund and the SPDR S and P Biotech exchange traded fund. It provided performance data and reference information that gave me a clear starting point.
That initial guidance saved me hours of screening. What might have taken days of reviewing reports, financial statements and sector data was reduced to an evening of targeted reading.
The Decision: Putting Money Behind the Idea
After reviewing historical returns, volatility and fees, I selected the ALPS Medical Breakthroughs exchange traded fund. I bought three hundred shares at about forty six dollars and thirty three cents each. Within a few days the position increased, and I saw a gain of around six hundred fifty dollars. A promising beginning, though still early.
More importantly, I had transformed a speculative idea into a structured and diversified trade. AI did not guarantee success, but it improved the quality of the process, helped manage exposure and encouraged me to reflect on risks.
What I Learned From Using AI: Benefits and Limits
What AI Did Well
Speed and efficiency. AI processed large amounts of data such as fund universes, sector exposure and historical performance in seconds. Tasks that once took hours now took minutes.
Objective second opinion. ChatGPT offered a balanced view and prevented over confidence. Its reminders about biotech risks helped me maintain realistic expectations.
Idea generation beyond familiar themes. AI encouraged me to think more broadly. Instead of focusing only on big tech, it helped me consider secondary beneficiaries like biotech, supporting a more diversified approach.
Lower friction entry. AI reduced the effort required to begin research, making the entire process more accessible.
What AI Could Not Do
Predict company specific risks. AI cannot access non public data such as clinical trial results, internal decisions or regulatory updates. These often determine biotech outcomes.
Guarantee returns. AI offers analysis, not certainty. Biotech remains volatile with binary outcomes, and an AI assisted trade can just as easily lose money.
Replace human judgment. AI lacks context about management quality, regulatory pressure and competitive dynamics. Human interpretation remains essential.
Make credible long term predictions. While AI reviews historical patterns, long term markets depend on unpredictable future conditions.
This balance between AI’s strengths and its limits shapes how investors should treat AI supported decision making.
Broader Implications: What This Means for Individual Investors
This experiment may be a single trade, but it reflects a larger shift in finance today.
AI as a Tool, Not a Replacement
For many investors, AI tools can filter noise, spotlight themes and support data processing. This is especially helpful for people with limited time.
However, human oversight remains crucial. Using AI alone for high risk sectors is like driving with autopilot during a storm. It helps, but you must keep control.
Diversification Gains Importance
Because AI highlights popular themes, many investors may converge on similar ideas, raising valuation risks. Thematic exposure through diversified funds may offer a safer path.
Risk Awareness and Acceptance
AI helps frame risk but cannot remove it. Investors must prepare for uncertainty and view AI as augmentation rather than a shortcut.
The Changing Finance Landscape
More investors rely on AI for screening and idea generation. Professionals and retail investors both use it as a productivity enhancer rather than a predictive oracle.
Regulatory concerns continue to rise regarding transparency, model bias, privacy and the potential for misuse. Investors need to stay cautious and informed.
AI is clearly becoming a part of financial research, but only as a tool within a larger framework.
Would I Do It Again and What I Would Do Differently
Yes, I would use AI again because its speed and analytical breadth match my long term and theme driven investment style.
However, I would diversify more widely, spreading exposure across themes such as AI infrastructure, clean energy and biotech. I would combine AI analysis with traditional research including financial filings and industry news. And I would maintain a cautious allocation, avoiding over exposure.
AI in 2025 as a Powerful Assistant, Not a Crystal Ball
My experience reaffirmed a core truth. Investing always contains both opportunity and risk. What changed here was the speed and depth of analysis that AI enabled.
AI helped me test an idea, build exposure and feel confident in the reasoning. The trade is still early and the future unknown. What matters most is the structure and discipline of the process.
If you try something similar, remember this: use AI as a compass, not a map. It helps guide the direction, but you must navigate the path yourself.
In investing, as in life, there are no certainties, only informed choices.
Nguyen Hoai Thanh
Nguyen Hoai Thanh is the Founder and CEO of Metaconex. With 12 years of experience in developing websites, applications and digital media, Nguyen Hoai Thanh has many stories and experiences of success to share.