AI Investment Research: The Role of Insight in Effective Decision-Making

As mentioned in the previous newsletter edition, artificial intelligence is everywhere but you cannot take it at face value. You need to audit the results you receive from an AI model because an AI model can make mistakes!

Though one skillset that AI models are trying to take on is insight. What do I mean by insights is being able to takeaway the interesting points and make a strategic decision from the information provided. As an investment researcher that has been doing market research and financial analysis since my students jobs back in the mid-2000s, I see the great benefit of using AI tools such as ChatGPT (OpenAI), Claude, Perplexity, and etc.

On another note, AI models might not have the right thing when it comes to insights hence it takes published information and let's be realistic, not every investor or business person will give all their secrets on their decision making to platforms or open source product.

As the University of Cambridge dictionary describes insightful as "showing a clear and usually original understanding of a complicated problem or situation".

The most effective way I have developed insight is through hands-on experience, meaningful interactions, and the mentorship I have received throughout my career.

The question leads to when you should use AI in relation to investment research?

When AI Is Working For Investment Research?

Artificial intelligence can assist in scraping, summarizing and even at some times doing an organization of several information / data points. The great thing when using AI to scrap data, it does the work that takes several hours and weeks to do in several minutes, which is quite amazing if you have done secondary research.

One thing it can also do greatly but not without auditing is summarising large research information as mentioned in the last newsletter. Another great thing that AI does is that it can combine information and data points in a formidable way that is very timely.

Overall, in relation to investment research, AI can do the bot work and more, which is great but does it do all the work? NO!

The Importance Of Human Experience And Knowledge

Human experience and knowledge is important since in business you are still working with other humans. Since many AI models are trained on human expertise and experience, some degree of bias is inevitable.

Although, human experience can teach a person to learn from its mistakes, which we must acknowledge AI is doing but we are still not at the full AGI (Artificial General Intelligence) stag. In other words, AI can still not apply all the knowledge and expertise as a human can.

A lot of times we listen and read about successful business professionals mentioning they learned the most from their failures. Can AI do that yet? Not necessarily, since the human has to tell it if it has made errors and address the key issues.

What Has AI Not Replaced In Investment Research

AI has definitely impacted investment research sector as I know during my decade plus experience but it has not yet completely replaced it.

Artificial intelligence lacks the intuition developed through hands-on investment research, which is essential for forming conviction and making context-driven risk decisions. As a result, it cannot fully replicate choices such as investing in a company based on confidence in its management team. AI cannot ensure if the data used is correct since it is being fed the data to make a decision.

Moreover, many companies secure significant investment despite having no product, raising billions solely on the strength of their management team’s experience and expertise. Would AI invest in that?

As of today, AI is a tool to be more productive but it cannot bring the INSIGHT that a human has based on experience and expertise.