Opinion: Gracy Chen, CEO, Bitget
Crypto traders are owned by information. Live prices flicker in microseconds, wallet trackers ping fresh whale movements, X-pivoting emotions every minute. For the average retail investor, maintaining often means deciphering all of this through a professional-level dashboard after closing from a full-time job. That is the real pressure point that will shape the next evolution of Crypto. It’s not another institutional product like BlackRock’s ETH staking app.
AI trading agents provide practical solutions to their challenges. They compress the flood of market data into a single practical recommendation that requires only simple input from users. Someone tell me you’ll set instructions: “If BTC drops by 5% while I’m sleeping, please lock profit.” AI agents pull those triggers and rehedges before the user’s alarm goes out.
Recent initiatives from Wall Street heavyweights such as BlackRock and Standard Chartered bring to life a welcome validation for Crypto Spot Markets, but their role is primarily infrastructure, helping money come and go. What really attracts users is the AI agents that make staying in the market easier, smarter and more sustainable.
Institutions chase access, traders long for intelligence
Rails are quickly becoming a product. JPMORGAN’s 2025 E-Trading Editor surveyed 4,200 buy-and-sell-side traders: 61% said AI will have more impact on the market than any other technology over the next three years.
The retailer talks the same thing. One in seven Crypto users are happy to pass their entire portfolio on the algorithm. Participants want a system to find patterns before humans flash.
Note as a rare asset
Here it is important to draw a clear line between the AI agent and the trading bot. Trading bots still dominate the orders and crush grids and momentum scripts. They are automated, but not intelligent.
The AI agent behaves differently. They rewrite the playbook in real time and blend sentiment scores, wallet forensics and personal risk budgets.
Traders can move from simple “buy/sell” orders to detailed inputs such as “reduce risk exposure for next month’s portfolio” and “Identify narrative rotations in early stages of memocoin.” Agents then consolidate market data and re-align their strategies on the spot.
Anxious trade-off between autonomy and accountability
Some critics have delegated execution to the software to agents’ users, claiming that if multiple agents chase the same signal at the same time, they can expand tail risk events.
Others warn that black box decisions will conflict with future rules regarding algorithm accountability. Past cycles show that productivity is gained when protective guards such as circuit breakers, kill switch permissions and transparent audit logs are included.
Exchanges that lack agent orchestration within next year run the risk of volume moving to the platform, and trading feels as easy as Spotify’s recommendations. Venture Capital and M&A will likely be a flood agent infrastructure and instead will be a market that will compress and reward the fees of transactions from clicks that expose agent-friendly APIs.
Related: Money never sleeps, Wall Street is awake
When AI agents start trading on different platforms in a flash, there is more activity to move to exchanges that can keep up with that speed. Market maker spreads tighten and price discoveries can accelerate until human reaction times become irrelevant.
Facilities desks are not exempt. Once the agent is able to prove the deterministic log, the tlaser routes the flow to the venue that offers the lowest “potential” pipeline. In stocks, Latency Wars has rebuilt the Exchange League table. Latency-to-Intelligence does the same with cryptography.
Lawmakers are less likely to ban agents from trading than banning stocks in the algorithm. Instead, it requests a verifiable audit trail for all inferences and actions.
A platform that burns encrypted logs into an agent framework converts compliance from headache to moat.
There are two options for exchange
The imminent contest is not a exchange with a bank. From a user’s perspective, it “equipped with me.” A platform with embedded personal trading agents opens up professional grade strategies for the masses, even if someone else handles the Fiat-on-Ramp.
The industry should stop shipping dashboards built for Bloomberg terminals and begin launching co-pilots who listen, learn and act for the benefit of everyday users. To summarise that stack, we need real-time data intake, fine-tuned language models, and a governance layer that allows humans to set up guardrails without hovering all decisions.
Regulated access can open doors, but the agent’s execution decides who to pass and waits outside.
Opinion: Gracy Chen, CEO, Bitget.
This article is for general informational purposes and is not intended to be considered legal or investment advice, and should not be done. The views, thoughts and opinions expressed here are the authors alone and do not necessarily reflect or express Cointregraph’s views and opinions.
