Today’s episode on Cryptic Talk reveals more on the roles of AI models, typically the AI trading bots, in modern-day crypto trading. We are joined by experts in the crypto space, namely, Ricks, who is Chief Brand Officer at QuackAI, Michael Cameron, co-founder and Chief Marketing Officer at perpetual trading platform Superp, and Nikolay Manolov, founder and Chief Executive Officer at AI development firm, ENVY.
Together, they discuss the current situation around AI in crypto trading, exposing the risks, and proffering solutions in the long-term.
AI in Crypto Trading: The Current Situation
If anything, the appearance of AI in crypto trading has been progressive. Every trader knows that the Fear/Greed Index is a major driving force in decision making among human traders, but AI models have helped these traders navigate their emotions even better. Instead of human sentiments like hope and optimism influencing trader actions, AI offers precision from in-depth analysis.
However, as interesting as their use cases sound, these crypto trading bots are not as autonomous as they seem. While they are an obvious upgrade over human traders, they require significant manipulation from humans to come up with meaningful outputs. Ricks is Chief Brand Officer at QuackAI, where the AI models developed are in close interactions with their human handlers, and, for him, AI models are like ‘fast cars,’ capable of doing so much but still needing ‘human seatbelts.’
This limitation of the current AI crypto trading bots is a result of their incomplete development. Incomplete, because they are basically algorithms that have been fed large quantities of data. Without context and advanced training using human interactions, AI bots will only be useful for analyzing volumes of data and executing pre-set instructions. For decision-making, the bots will still be heavily reliant on their human-AI collaborations.
But the lack of autonomy of AI trading bots is only one of the main issues around AI in crypto trading.
AI Trading Bots: Risks and Challenges
Artificial Intelligence models in the present crypto trading space have changed the landscape significantly. With AI bots in the crypto trading landscape, the playing field is no longer level. It is an advantage for traders who have access to and knowledge of these AI trading bots. For other crypto folk, it is tipped against them.
For one, there are open-source crypto trading bots like GMGN AI and Banana Gun bot on Solana’s pump.fun that allow users to snipe newly-launched tokens, especially meme coins, as soon as they hit the exchanges. Following pre-set conditions, the trading bots can execute sell positions within seconds of a stop-loss situation, promptly causing mass liquidation and a market crash.
Michael Cameron, who is Chief Marketing Officer and co-founder at Superp, identifies the disparity that such market crashes cause. Such situations cause retail traders to lose their capital to the market, as they do not have the leverage that the bigger traders, like institutional traders, have. Sure enough, the AI tools are available for all traders to use; but their effectiveness for each trader still depends on how large their positions are in the market.
That’s where the Superp initiative comes in. The product essentially platforms perpetual markets for retail traders, allowing them to trade up to 10,000x leverage with no risks of liquidation.
In a sense, the introduction of AI has widened the disparity between retail traders and the whales in the space. Then again, fine-tuning the policies within which AI trading bots operate could level the playing field without eliminating AI as a viable development for crypto trading.
Crypto Trading Bots: The Solution is in AI Regulation
For some crypto users, the solution to curb the excesses of trading bots is to ban the bots from the DeFi trading space. On one hand, it sounds like an actionable plan, since such bots could be manipulated by bigger players in the trading space to engineer massive price crashes. The bots simply follow such pre-set parameters as stop-loss and take-profits, and a group of big traders could short the market, leading to a domino effect where all bots start to liquidate, at the expense of retail traders.
In fact, that seems to be the situation we have had in 2025, where the market crashes have come rather suddenly. Still, on the other hand, an AI trading bot ban is not the best way forward.
Already, Nikolay Manolov is founder and Chief Executive Officer at ENVY, where they are looking to develop the next generation of AI tools that will outperform even human traders. And with the increasing functionalities of AI models all over the world, that goal is not far-fetched.
While he concedes that the challenges around ethical use of AI tools will be tough to solve, he maintains that the flux of AI into crypto trading simply opens up another layer of opportunities to traders everywhere. Like other technological revolutions, some people will take advantage of it, while others won’t.
Ricks from QuackAI, on the other hand, opines that including ‘intent validation and on-chain pre-trade policies’ during AI development and deployment is the way to go, not banning the tools. It may take a rough few years to get AI trading bots to level the crypto trading field, but that is definitely the way to ensure ethical use of such tools in the market.
Key Takeaways
The flux of AI tools, particularly crypto trading bots, have switched up the situation in the market significantly. They are still dependent on human inputs for efficient decision-making, and therein lies their limitations. In the wrong hands, the AI trading bots can be used to manipulate the markets by big traders.
So, the solution? AI regulations, and that won’t come very easily.
Disclaimer: This article is based on an interview and reflects the personal views and opinions of the featured speaker. It is intended for informational purposes only and should not be considered financial, investment, or legal advice. Readers are encouraged to conduct their own research and consult with qualified professionals before making any financial decisions.
