A recent behavioral study of Mexc research reveals a spectacular generational change in cryptographic trading. Depending on the platform analysis of more than 780,000 users, 67% of generation Z merchants (18 to 27 years) already use or actively adopt tools powered by AI.
This cohort adopts automation for purposes beyond convenience, to manage risks, reduce emotional prejudices and delegate strategic decisions under volatile market conditions.
The adoption of AI rises among merchants of the Z generation on Mexc
Mexc’s Q2 2025 behavioral intelligence report shows that two -thirds of users of the Z generation have activated at least a strategy based on a bot or rules during the last 90 days.
However, use goes further than the deployment of bot. These users actively incorporate AI into their trading behavior, 22.1% joining with AI tools at least four times a month.
Based on the report, Gen Z now represents 60% of all bot activations on the platform.
This cohort is on average 11.4 days a month by interacting with AI tools, which represents more than double the commitment of users over 30 years.
Their use is also intentional, the study showing that 73% of merchants of generation Z activate bots during volatility points but closed them on the markets at low volume or laterally. For them, AI is not a general solution. It is rather a selective and situational advantage.
Emotional regulation and delegation: the edge of generation Z
Mexc Research’s results suggest that, beyond the confidence of AI, Gen Z uses it as a psychological buffer. Merchants using bots saw a reduction of 47% of panic sales during market stress, compared to those who are negotiated manually.
Rather than reacting to each Twitch on the market, Gen Z configures automated strategies with clear rules, then retreats.
This method, described in the report as a “structured delegation”, reduces the fatigue of decision and cognitive overload and wider digital behavior mirrors in the workplace.
According to a May 2025 survey of Repume.org, more than 50% of workers of the Z generation consider Chatgpt as a colleague or a “friend”. AI goes beyond the replacement of human judgment to improve the emotional discipline of these users.
Risk management redesigned
Change to AI also transforms how the risk is managed. Users of the Z generation who engage with AI trading tools are:
- 1.9x less likely to make impulsive transactions in the first three minutes of the main events on the market
- 2.4x more likely to implement stop and shooting strategies
- 58% of the use of Bot Gen Z occurred during the points of the internal volatility index of Mexc
These models reflect a new style of semi-automated trading, where bots act as failures in moments of high emotion or uncertainty. The AI goes beyond the acceleration of trades, applying discipline when it matters most.
Gen Z vs millennials: two commercial operating systems
In addition, the intergenerational analysis of Mexc reveals a fundamental divergence in commercial psychology. On the one hand, the millennials are looking towards structured approaches and focused on the thesis that strongly use graphics, research and manual surveillance.
On the other hand, the Z generation approaches trading as they use Discord or Tiktok – fast, responsive and dependent on the interface.
Rather than long form strategies, generation Z promotes modular and customizable tools that allow flexible control. Their commercial activity is shaped by emotional bandwidth and cycles of attention.
They activate and deactivate automation according to the mood of the market and the levels of personal stress, a foreign behavior to the most static strategies of the older cohort. This reflects wider models in the trading of copies, decision -making led by influencers and investment communities focused on social.
This report suggests that generation Z already builds the future of cryptographic trading rather than waiting for it. However, in their quest to prioritize speed, clarity and emotional control, users must also be wary of blind confidence.
Excessive dependence on AI tools can introduce new risks, in particular algorithmic bias, defective data sets and the opacity of the model, placing systemic threats.
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