Today, I watched a speech by former Google CEO Eric Schmidt, and his description of the importance of #AI is thought-provoking. He mentioned that the development of #AI technology in the next decade will directly determine the future of the next hundred years.

Back in the internet era, when I looked at a startup project, my first reaction was to ask, "How big is your market?"

Because the essence of internet business is a "people" business: how many people will use it, and how much are they willing to spend. For example, WeChat, Douyin, and Amazon all follow the same logic—capturing a massive user base and then finding ways to monetize user value.

But the #AI era is different. Schmidt said that #AI is like electricity, like fire. It is not a "consumer product," but a "productivity tool" that can directly create results. This means that the market size of AI can no longer be calculated using "number of users × average transaction value," but rather by looking at how much of the "wage pie" it can penetrate.

Take coding as an example. There are only about 30 million programmers worldwide, which doesn't sound large. But these individuals have high salaries, with a total market size of around 500 billion dollars. The value of #AI coding tools lies in whether they can capture a portion of this 500 billion dollar cake.

For instance: if AI coding tools can replace 10% of a programmer's work, that would be a value of 50 billion dollars. If it replaces 30%, that's 150 billion dollars. In a more extreme case, if it achieves full automation, it could completely rewrite the industry landscape.

This is why, even though the programmer group itself is not large, #AI programming is still highly favored by the capital market. Because it directly connects to "wage costs," and wages represent the most tangible market.

Moreover, this logic applies not only to programming. In the future, lawyers, doctors, designers, investment banking analysts… these high-salary groups are all backed by huge wage pools. The more #AI can take away, the larger the market.

So in the #AI era, when I look at a project, I will no longer ask "how many users," but will first ask, "Who can it help save money for, and how much can it save?" Because #AI is a silicon-based employee, and the real competitors are not other internet applications, but "human labor."

From an investment perspective, the most noteworthy sectors are those with the largest wage pools and highly standardized job content. Programming is just the first explosion; the next could be legal documents, financial research, medical diagnosis, and even design processes in manufacturing.

In other words, the investment logic of #AI has shifted from "user economy" to "labor economy." Whoever can replace the most human jobs will capture the largest market. Exploring innovations in #AI application fields from this perspective will yield great potential, and finding investment targets will become clearer. 🧐

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