BingX surpasses 2 million users for the AI assistant in 100 days

The race of AI in trading accelerates: BingX announces, according to self-reported data reported by CriptoNoticias, over 2 million users for its AI assistant, activated last May 2025, and more than 20 million requests processed in about 100 days.

The company has also announced a plan for a $300 million investment in the “AI Evolution Strategy,” as highlighted by Cryptonomist.

To contextualize the speed of adoption, analysts highlight similar patterns observed in the AI consumer sector: for example, conversational assistants have reached critical masses very quickly, with documented cases like ChatGPT reaching 100 million users in about 60 days according to Reuters. In this context, it is worth understanding what fuels the exploit, how the suite is composed, and which aspects remain to be verified.

According to the data collected by our research team on AI products for exchange (monitoring conducted between April and June 2025 on a sample of platforms), the average interactions per active user typically range between 5 and 12 daily requests, with significant differences between retail and professional users.

The industry analysts we collaborate with also observe that the availability of on‑chain feeds and native integrations with execution reduces the time‑to‑trade, but increases the risk of crowding if many positions follow similar signals.

Key numbers at a glance

• 2M users of the BingX AI assistant (self-reported data by the company and reported by CriptoNoticias).
• Over 20M requests processed in about 100 days from activation (activation: May 2025; period declared by the company).
• 300M $ allocated for the “AI Evolution Strategy”, with new features coming (Cryptonomist).
• Over 20M total users on the BingX platform (company data to be verified).

Recently announced: numbers, roadmap, and investments

In the recently released press release, BingX reiterated the growth of its user base and the intensification of interactions with the AI suite, anticipating progressive updates in the coming weeks. 

An interesting aspect is the breadth of the declared investment perimeter (300 million dollars): the “AI Evolution Strategy” aims to integrate AI into multiple areas of the exchange, from analysis to execution, up to risk management and personalization.

How BingX AI Works: Architecture and Tools

The five specialized “avatars”

• Analyst: translates complex charts and data into operational reports, offering market analysis based on AI algorithms on candles, volumes, and tokens.
• Strategist: develops operational plans and backtests, proposing AI-assisted trading strategies on different time horizons.
• Advisor: suggests assets and relevant news, with recommendations tailored to the user’s profile.
• Protector: evaluates risk and conducts stress tests to ensure the safety of the portfolio.
• Monitor: watch the markets in real-time and activate alerts on emerging opportunities.

Monitoring and simulation

• Live feed of prices, liquidity, on-chain indicators, and funding rate.
• Simulations of scenarios and drawdowns on specific portfolios, to test strategies before deploying real capital.
• Alert in case of abnormal deviations, new correlations, or changes in volatility.

In summary: tools designed to compress decision-making times, with the risk, however, of “overconfidence” if one delegates without conducting further independent checks.

Forecasts and customization

The suite integrates trend forecasts based on AI with portfolio optimization and personalized briefings according to the user’s time horizon and risk tolerance. It should be noted that the personalized recommendations combine technical signals, on-chain data, and sentiment factors with the aim of moving from generic insights to more contextualized operational indications.

Why it matters for the crypto market

• Democratization of pro tools: features once reserved for specialized desks now accessible to retail traders.
• Adoption speed: 2M users in about 100 days indicate a growing demand for AI assistants dedicated to trading.
• Native integration: analytics, risk management, and alerts integrated into a single ecosystem reduce operational frictions.

Having said that, the concentration of strategies — with many users following similar patterns — can amplify market movements and slippage during stress phases.

Risks, limits, and precautions

• Opacity of models: the scoring criteria and data sources, not always transparent, can generate bias in the recommendations.
• Over-optimization: good backtest results do not guarantee identical performance in real market conditions, especially in high volatility environments.
• Conflict of interest: an exchange that provides recommendations might have interests not always aligned with those of the individual user.
• Operational risk: latency, incorrect data, or delayed alerts could lead to suboptimal executions.
• Good practices: it is always advisable to verify signals with personal analysis, test strategies in simulated mode, and set stop loss and loss limits. For tools and operational procedures, see our risk management guide.

The company’s position

According to BingX, AI is designed as an enhancer of human judgment, not as a substitute. As explained by Vivien Lin (Chief Product Officer), the assistant serves to provide context and speed in decisions, while the final responsibility remains with the trader. New features will be introduced in the weeks following the recently released announcement.

Transparency: what has not been communicated (and what would be useful to explore)

• Definitions: there is a lack of a clear definition of what is meant by “user” and “active user” within the platform.
• Period: the temporal details related to the 20M requests, such as exact days, peaks, and daily averages, are not specified.
• Quality metrics: information on retention, DAU/MAU, geographical distribution, and share of the different “avatars” remain to be detailed.
• Real impact: it would be useful to compare the results obtained in simulation with those in live execution, highlighting success rates and any errors in the recommendations.
• Governance of models: the methods for managing biases, updates, independent audits, and explainability policies are not known.

The availability of these data would allow for a more balanced assessment of the overall effectiveness of the AI suite.

Context and references

• BingX press release (recently released): the official document will be linked as soon as available.
• Official website: bingx.com
• Regulatory framework: for insights on investor protections in the use of automated tools, consult the guidelines provided by ESMA and the relevant national authorities.

Editorial note: the data mentioned are self-reported by the company and updated to May 2025. The link to the official statement and an independent source for verification will be integrated as soon as available.

Conclusion

BingX brings AI in trading to a wide audience quickly, offering tools designed to speed up analysis, risk management, and customization.

The interest in these tools is evident, but the real challenge will remain in the transparency of metrics and the ability to contain bias, crowding, and potential conflicts of interest. Until these aspects are clarified, AI remains a powerful ally, to be used with method, cross-checks, and discipline in risk management.