Human Traders Still Have Edge Over AI

Despite artificial intelligence (AI) experiencing a surge in popularity, impacting nearly every industry, including the stock market, it can’t take over trading just yet. However, many believe otherwise. Because of the rapid advancements in large language models (LLMs), some think that machines could soon dominate the trading space. But this isn’t happening any time soon.

Limits of AI in Trading

It is widely known that AI is already handling a variety of tasks quite effectively. However, its capabilities are often exaggerated. Take, for example, customer service automation. Many leading banks like JPMorgan and Capital One use AI-powered chatbots to enhance customer interactions, which lightens the load on human employees, leading to reduced operational costs. Some users may find it annoying, but is highly beneficial for companies and workers. Users should try to accept the machines' help since they can offer faster answers, saving the time of users as well. It’s just a matter of time before chatbots become fully accepted by society.

As AI now plays an important role in analytics, processing massive amounts of data, news and financial events, it has started being used in trading as well. For example, Bloomberg introduced BloombergGPT last year — a large language model that was designed specifically for finance. It is a great technology but tools like this are only capable of performing junior analyst tasks — they’re not enough to replace human expertise. This is because successful trading relies heavily on strategic thinking, creativity and intuition, which are qualities that can’t be associated with robots yet.

Related:How AI Deepfakes Threaten Cybersecurity

Trading Strategies and AI

Speaking of qualities essential in trading, many argue whether to prioritize speed or intelligence. To answer this question, it’s necessary to consider different types of trading. High-frequency trading (HFT), for example, is all about speed. Success in HFT mostly depends on hardware quality, AI is a great benefit here but isn't necessarily a requirement. That is why HFT traders invest a lot in advanced servers that are located near exchange data centers to get a competitive advantage where milliseconds matter.

At one point, high-frequency traders showed interest in using AI, mainly deep learning networks, to analyze the microstructure of order books and predict behavior over slightly longer time frames. But as this technology became more widespread, market inefficiencies decreased and, unfortunately, profit opportunities reduced. 

Related:How to Use AI for an Ethical and Sustainable Future

On the other hand are long-term strategies where “playing it smart” is key, but AI's role is once again still limited. Trading is inherently a game of probabilities, which requires human insight, which AI hasn’t yet mastered. While traders may not always make perfect forecasts, staying updated on market news and trends allows them to make informed decisions. This is why, in many cases, human traders can still outperform machines. However, long-term strategies have their own challenges, such as the time required to test and validate approaches. And even in these cases, traditional methods like backtesting and historical data analysis are still effective, so there’s no need for the latest AI advancements.

What if AI Becomes Truly Intelligent?

Despite all this, it's always worth exploring new tools and AI may still prove useful in trading. In the coming years, the technology will undoubtedly grow more powerful and its role in finance will increase as well. However, truly significant changes in this technology are still at least half a decade away. Perhaps when artificial general intelligence (AGI) emerges, we will see new use cases for it. But it is at least five to seven years away, possibly even longer. Human intelligence will remain irreplaceable in trading until AGI becomes a reality.

Uniquely human qualities remain most important and effective in trading, which is a competitive arena where intuition, experience and creativity play crucial roles in pursuing profits. AI cannot yet replicate these, which is why the final truly successful decisions will remain in the human hands for a long time.