AI in the crypto industry: still a powerful tool, not a replacement for the expert
Artificial intelligence has firmly entered the crypto industry, but its role at the current stage is that of an accelerator, not an independent player. Even tasks such as writing code and monitoring exchanges remain under close human supervision. Let's figure out why this is happening and where the real boundaries of AI application lie.
What tasks have already been delegated to AI?
In practice, the application of AI in crypto companies boils down to two main areas: content marketing and accelerating development. In content marketing, neural networks are used to gather news and analyst opinions, generate posts, analyze trends on TikTok, and even create videos. In development, AI agents take on monitoring changes in exchange APIs and writing code.
The key point: all these processes occur under the supervision of specialists. AI is an automation tool that reduces the time spent on routine operations but does not make final decisions. As practitioners note, even when writing code, agents work in conjunction with developers who check and adjust the result.
Tools and boundaries of trust
The set of tools is selected through trial and error. In development, VS Code with Codex and Claude Code are actively used. For video generation, Kling and Eleven Labs are used, which, according to expert estimates, offer the best quality-to-cost ratio per unit of finished material. Lovable is used for creating landing pages.
No serious AI errors that would have cost companies dearly have been recorded so far. The reason is simple: artificial intelligence works in conjunction with humans. It is not an independent agent but a powerful tool for automating and accelerating processes, where control remains with the specialist.
As for trusting an AI agent with real transactions, the approach here is based on classic risk management. The allowable loss volume and the agent's level of access to data are determined individually, based on the risk profile. This is not a matter of technology but of financial discipline.
Symbiosis of tools: each covers its own area
Experienced analysts use a whole arsenal of AI tools, distributing tasks among them on the principle of "each covers its own area." For example:
- ChatGPT in conjunction with CoinGlass — for processing data on open interest, liquidations, funding rates, and the ratio of longs to shorts. Instead of an hour of manual data compilation, it takes 30 seconds for a ready picture.
- Grok, integrated into X — for real-time monitoring of crypto Twitter. Early signals and leaks appear there, and timely access to them provides a head start of a couple of hours to assess their reliability.
- Claude — for the strategic direction of the day.
As a result, the tools complement each other: Grok provides speed and access to sentiment, ChatGPT handles routine chart analysis, and Claude handles strategy. The outcome: analysis takes not a couple of hours a day but just 15 minutes.
My conclusion as an analyst: AI in crypto is not a replacement but a scaling of expertise. Those who learn to build an effective "human + AI" pairing will gain a tremendous advantage in speed and quality of analysis. But relying on "blind" trust in agents is a path to capital loss. Control and critical thinking remain the main assets of a trader and analyst.