Behind the Screenshots of Sharing Profits: The Real Division of Labor Between AI and Humans

Recently in the Gate.io community, you often see people sharing AI profit screenshots. Some catch a rebound wave, others successfully avoid downturns—it seems like AI has really become a "money-making machine."

But if you look carefully, you'll discover a pattern: those who consistently make stable profits don't completely rely on AI.

Their operating model typically works like this: AI handles analysis, humans handle judgment.

For example, when researching Bitcoin or Ethereum, AI can quickly summarize market data: on-chain fund flows, exchange inflows, sentiment indicators, and so on.

If people had to organize this information manually, it might take half a day. But AI can generate it in seconds.

So traders can focus more energy on strategy rather than data collection.

I tested an interesting approach myself: have AI provide three market scenarios—uptrend, sideways movement, or downtrend.

Then develop a plan based on the highest probability scenario. If market movement aligns with AI's judgment, execute; if it doesn't, stop loss in time.

The biggest benefit of this method is: it reduces emotional trading.

Because AI doesn't experience FOMO, and it doesn't panic.

So those people sharing profit screenshots aren't really showing off how magical AI is—they're demonstrating a new trading model: humans handle decision-making, AI handles information processing.

The future trading world may not be "human vs market," but rather "human + AI vs market."#Gate广场AI测评官