Today, while chatting with GPT, I noticed quite an interesting contrast behind the AI boom.

CN
BITWU.ETH
Follow
11 hours ago

Today, while chatting with GPT, I saw an interesting contrast behind the AI craze.

On one side, there is strong trend data:

For example, the data I recorded earlier, the Stanford HAI's 2026 AI Index shows that generative AI will reach about 53% population-level adoption within three years, spreading faster than PCs and the internet;

Microsoft's 2026 Work Trend Index also emphasizes that AI Agents are entering organizational workflows, and human value will increasingly concentrate on goal setting, judgment, supervision, and accountability for results.

But today I found another side that is quite calm and realistic:

Gartner predicted in June that over 40% of Agentic AI projects will be canceled by the end of 2027 due to rising costs, unclear business value, or insufficient risk control.

This is actually similar to crypto and blockchain; a trend can be certain, but the translation into commercial value, company profits, and asset prices has a long road in between.

I mention this case because I feel that in investments, we easily jump from narrative directly to positioning.

What feels most important now is that we must go through a chain of evidence, counter-evidence, odds, and position matching in between. Trends can only provide research qualifications, but cannot directly provide heavy position qualifications.

So for AI investments, I currently have three disciplines:

1️⃣ Do not equate "correct technology trend" directly with "all related assets are worth buying."

The AI direction is very likely a long-term trend, but trends can only provide research qualifications and cannot directly provide heavy position qualifications.

2️⃣ Instead of chasing concepts, it is more important to see who can actually generate cash flow.

Those who can reduce costs, improve efficiency, lock in customers, and form pricing power are closer to investment value. Many Agent projects may fail, but the infrastructure, platform layer, workflow entry points, data, and security layer may actually benefit from the trial-and-error wave.

3️⃣ Positions are not for expressing beliefs but for validating hypotheses.


免责声明:本文章仅代表作者个人观点,不代表本平台的立场和观点。本文章仅供信息分享,不构成对任何人的任何投资建议。用户与作者之间的任何争议,与本平台无关。如网页中刊载的文章或图片涉及侵权,请提供相关的权利证明和身份证明发送邮件到support@aicoin.com,本平台相关工作人员将会进行核查。

Share To
APP

X

Telegram

Facebook

Reddit

CopyLink