Opinion by: Gracy Chen, CEO, Bitget
Crypto traders are drowning in information. Live prices flicker by the microsecond, wallet trackers ping fresh whale moves, and sentiment on X pivots by the minute. For the average retail investor, keeping up means decoding all this through pro-level dashboards — often after clocking out from a full-time job. That’s the real pressure point shaping crypto’s next evolution — not another institutional product like BlackRock’s ETH staking app.
AI trading agents offer a practical solution to that challenge. They compress the flood of market data into a single, actionable recommendation that only needs a simple input from the user. Say someone sets the instruction: “Lock in gains if BTC drops 5% while I’m asleep.” The AI agent pulls the trigger for them and re-hedges before the user’s alarm goes off.
While the recent initiatives from Wall Street heavyweights such as BlackRock and Standard Chartered bring a welcome validation for crypto spot markets, their role is largely infrastructural, helping money move in and out. What will truly keep users engaged are AI agents that make staying in the market easier, smarter and more sustainable.
Institutions chase access, traders crave intelligence
Rails are quickly becoming a commodity. JPMorgan’s 2025 e-Trading Edit surveyed 4,200 buy- and sell-side traders: 61% said AI will influence markets more than any other technology over the next three years — more than API integration, more than blockchain itself.
The retail side tells the same story. One in seven crypto users is happy to hand their entire portfolio to an algorithm. Participants want systems that spot patterns before humans blink.
Attention as a scarce asset
Drawing a clear line between AI agents and trading bots matters here. Trading bots still dominate order books, grinding out grid or momentum scripts. They are automated, but they are not intelligent.
AI agents operate differently. They rewrite their playbooks in real time, blending sentiment scores, wallet forensics and personal risk budgets.
A trader can move from simple “buy/sell” orders to detailed inputs like “reduce my portfolio’s risk exposure over the next month” or “identify early-stage narrative rotations in memecoins.” The agent then synthesizes market data to recalibrate strategy on the fly.
The uneasy trade-off between autonomy and accountability
Some critics argue that delegating execution to software strips users of agency and could magnify tail-risk events if multiple agents chase the same signal simultaneously.
Others warn that blackbox decision making will collide with forthcoming rules on algorithmic accountability. Past cycles show that productivity gains win once safeguards like circuit breakers, kill-switch permissions and transparent audit logs are embedded.
Exchanges that lack agent orchestration within the next year risk watching volumes migrate to platforms where trading feels as effortless as Spotify recommendations. Venture capital and M&A will likely flood agent infrastructure, compressing click-to-trade fees and rewarding marketplaces that expose agent-friendly APIs instead.
As AI agents start trading across different platforms in a split second, more activity will shift to exchanges that can keep up with that speed. Market-maker spreads will tighten, and price discovery could accelerate until human reaction time becomes irrelevant.
Institutional desks will not be exempt. After agents can prove deterministic logs, treasurers will route flow to whichever venue offers the lowest “latency-to-insight” pipeline. In equities, latency wars reshaped exchange league tables; latency-to-intelligence will do the same in crypto.
Lawmakers are unlikely to ban agent trading any more than they banned algorithmic equities. Instead, they will demand verifiable audit trails for every inference and action.
Platforms that bake cryptographic logging into their agent frameworks will convert compliance from a headache into a moat.
Exchanges have two choices
The impending contest is not bank versus exchange. From the user’s perspective, it’s “equip me” versus “overwhelm me.” Platforms that embed personal trading agents will open professional-grade strategies for the masses, even if someone else handles their fiat on-ramp.
The industry should stop shipping dashboards built for Bloomberg terminals and start launching co-pilots that listen, learn, and act for the benefit of everyday users. Putting that stack together takes real-time data ingestion, fine-tuned language models, and governance layers that let humans set guardrails without hovering over every decision.
Regulated access may open the door, but agentive execution decides who walks through and is left waiting outside.
Opinion by: Gracy Chen, CEO, Bitget.
This article is for general information purposes and is not intended to be and should not be taken as legal or investment advice. The views, thoughts, and opinions expressed here are the author’s alone and do not necessarily reflect or represent the views and opinions of Cointelegraph.
