For many people today, the term “AI trading bots” conjures visions of effortless profits; a golden ticket to market mastery that doesn’t require breaking a sweat. Fueled by the AI boom and the relentless buzz around this technology, some expect these bots to single-handedly revolutionize trading.
However, as with many overhyped innovations, the reality is a lot more nuanced than that. Let’s dive into what AI trading bots can actually achieve, their limitations, and just why public expectations are running ahead of reality in this field.
The Role of AI in Trading
Artificial intelligence has been an important part of modern trading for a while now, though its real-life applications are not as catchy and dazzling as many might imagine. Instead of flashy systems that effortlessly dominate markets as if by magic, real AI applications are a lot more subdued and precise.
In high-frequency trading (HFT), for example, AI has been seeing actual use for the past 5-7 years. Unlike traditional low-latency approaches that rely on faster hardware, AI algorithms can be leveraged to predict the microstructures of order books over relatively short intervals, ranging from hundreds of milliseconds to a couple of seconds. This gives traders an alternative way to execute trades that doesn’t involve constantly chasing after faster hardware (which can be quite pricy).
That said, while this was once a good opportunity for early adopters, the growing adoption of AI has made the space a lot more competitive, shrinking margins for new entrants.
Beyond HFT, AI’s ability to analyze historical data allows it to identify subtle patterns and correlations that human analysts might miss. This allows traders to keep an eye out for otherwise unexpected relationships between assets or predict how specific events could potentially impact market behavior.
Furthermore, artificial intelligence has a role to play in event-driven strategies, once again due to its ability to process vast streams of news, economic reports, and market updates at great speed. It reduces the need for junior analysts who would normally cover all of his work. And in turn, this enables traders to cover more instruments.
However, I must note that AI based on Large Language Models is currently unsuitable for making consistently successful trading decisions. So the successful execution of these strategies still comes down to human judgment or simpler, more controlled approaches that aren’t driven by AI.
Public Perception vs. Reality
For many traders, the allure of AI trading bots lies in their perceived simplicity and promise of effortless profits. But, in truth, this way of thinking only sets them up for disappointment. Relying on blind hope without understanding how these tools — or the market in general — operate doesn’t just threaten losses; it guarantees them. This is a ruthless and highly competitive environment, and if you don’t know who’s paying for the dinner, chances are that it’s coming out of your pocket.
Many of the trading bots available for public use promise more than they can deliver. The simple reality is that there are no AI trading products of high quality that are actually available to retail clients. The ones available on the market mostly rely on simple algorithms or are outright frauds and scams.
And the niche strategies that actually work don’t depend on AI at all. They are primarily built on deep expertise and understanding of specific markets and use mathematical models. But AI models based on LLM have little to do with it.
Private firms may leverage advanced AI models, but we know little to nothing about what they actually do in practice. If they even use such things at all, and not just saying it for the image. If someone has found a way to make it work, they are certainly not sharing the knowledge with the rest of the market.
AI’s Limitations and the Importance of Human Oversight
Despite AI’s potential and the admittedly very real cases where it’s genuinely useful, it is undeniable that this technology has clear limitations in trading. Recognizing this and avoiding over-reliance is crucial if you wish to sidestep potential pitfalls.
One major limitation of artificial intelligence is that, for now, it can only be applied in a very narrow range of supportive tasks. AI can simplify the work of junior analysts, act as a replacement for a call center, or solve specific mathematical problems. But even that last one relies more on mathematical models developed decades ago rather than LLMs that are all the hype these days.
Artificial intelligence is not, however, in any way good at creating trading strategies, since it generally struggles with understanding things like time and causality. AI models are only as good as the data they’re trained on.
For example, that’s why it’s pretty decent at processing human language – there’s an endless supply of texts to be found on the Internet. But designing profitable trading strategies is something that’s very much outside of AI’s capabilities at its current stage of existence.
No, successful strategies are still created in the traditional way, not generated by a ChatGPT request. There are many models and approaches to trading. Intuition exists as one of them. I know (very few, but still) highly successful intuitive traders.
When it comes to creating trading algorithms—specifically the act of creating, inventing something new, or experiencing a breakthrough in understanding a particular market—intuition, like many other factors, can play a role.
However, in a launched and operating algorithmic trading system, intuition and any arbitrary decisions not only have no place—they are akin to death.
And while artificial intelligence can assist in smoothening certain processes out, it is only utilized in a secondary fashion. AI trading bots are simply not yet at the level where they can confidently replace the decision-making of human traders.
The Future of AI in Trading
As AI technology continues to advance, its role in trading is likely to expand as well, but for now it is going to primarily as a support tool and nothing else. Speeding up programming, assisting in preparing analysis, automating repetitive routine tasks — that sort of thing is very possible, yes.
However, for AI to start generating profitable trading algorithms at the push of a button is a completely different matter. It’s going to require a far more fundamental breakthrough. Specifically, the proper emergence of AGI (Artificial General Intelligence), and we don’t understand how much time remains until this event.
And even when AGI actually comes around, this technology won’t be exclusive just to you. If AI learns to do something well, that capability will quickly become available to countless competing traders, all chasing the same opportunities. The cut-throat environment isn’t going to go anywhere.
So traders shouldn’t expect that they’re suddenly going to have it easy. You can be absolutely sure that you won’t get a robot for a $20 monthly subscription that will trade consistently and successfully just for you. No one can ever systematically make a profit without effort.
Regardless of what the future brings, for now, the key rule remains unchanged: AI is not a substitute for a comprehensive understanding of the market. Yes, it can offer considerable analytical power that you certainly can take advantage of if you want, but for the moment it’s the human trader who ultimately makes the decisions.