Why Did an AI Application Going Global Lose 3 Million Yuan in Two Years?

A couple of days ago, an entrepreneur did a post-mortem: the team was taking AI applications global and lost 3 million yuan in two years.
Their original idea was simple: since AI can develop software quickly, they should make more products, launch quickly, run ad traffic, and replicate those independent developers earning over ten thousand dollars a month, scaling the business up.
What happened? They did make money early on, but could never replicate growth, and eventually the team disbanded.

Where did the problem lie?

01A Big Misconception: Lower Cost of Building a Product Does Not Mean Lower Cost of Selling It

Many people assume that because AI lowers development costs, the probability of entrepreneurial success will increase. But there is a big misconception hidden here:

The cost of building a product has gone down, but that does not mean the cost of selling it has gone down.

In the past, having a technical team that could build a product was itself a threshold. Now, AI enables more people to cross that threshold.
But when everyone can build products, competition changes.
You build an AI writing tool – others can too; you develop an AI image generation app – competitors may produce similar functionality in a matter of days.
Products keep multiplying, but users do not. To acquire customers, you have to spend money on traffic; once you have paid for users, you have to find a way to make them stay.

02Users Being Willing to Try AI Does Not Mean They Are Willing to Pay for It Long-Term

This leads to the second question: why would users keep paying?

In 2026, the subscription app report released by subscription management platform RevenueCat showed that, among the app samples studied, the median annual subscription retention rate for AI apps was 21.1%, compared with 30.7% for non-AI apps.
This does not mean all AI apps fail to retain users, but it does point to something worth being vigilant about:

Users being willing to try AI does not mean they are willing to pay for it long-term.

If your product merely makes users feel novelty but does not continuously solve a real problem, then no matter how low the development cost is, it will be hard to form a stable business.

03The Real Watershed for AI Startups Is Shifting

So the real watershed for AI startups is shifting.

In the past, you might first ask: what product can I develop?Now, you should first ask: who has a problem they are willing to pay to solve? Does this problem occur frequently enough? After it is solved, why would users continue to use my product?

AI is making software production cheaper and cheaper, but what is truly scarce is shifting from development capability to customer value.

This is also why some entrepreneurs keep using AI to develop new products yet never find growth, while others simply embed AI into their existing business and find it easier to create value.

In the next episode, we will continue with an even more pointed question:
If AI can let you build ten pieces of software a day, why might you actually be further away from making money?