小公司为什么在 AI 时代很困难, HSK4 reading

In spring 2025, many Chinese internet companies published financial reports (reports of company income published every three months). Unlike big companies, smaller ones rarely say separately how much money AI earned. For example, Zhihu mainly earns from paid content and ads; iQiyi mainly from memberships; Weibo mainly from ads. These platforms have made money in much the same way for years. So AI has not yet become an important new source of income for them.

But that does not mean they do nothing with AI. After ChatGPT became very popular at the end of 2022, smaller companies also moved quickly. Zhihu built AI Q&A; iQiyi built an AI assistant; Weibo built AI search. These AI tools also help inside the company, for example checking content and improving work efficiency.

The problem is that most of these AI tools can only be used inside their own apps, and struggle to bring many new users and new income. Compared with big companies, smaller firms' AI is not strong enough, and they do not have much money for advertising. Users prefer the best and newest AI, so smaller companies find it hard to compete. Many AI projects are exciting at first, then slowly go quiet. AI looks more like a small feature added to old business, not a new way to make money.

A bigger difficulty is the huge gap in money and resources. Big companies like Alibaba and ByteDance can spend a huge amount on AI each year. Their main businesses earn well, and they can get more money from the market, so they can invest for the long term. Smaller companies earn much less each year. If they tried to go all-in on AI like big firms, their money would run out quickly. AI large models (very large AI programs), AI apps, and coding tools increasingly look like a game only rich big companies can stay in long term.

Mid-size companies can sometimes find a path. For example, Kuaishou's "Kling" focuses on AI video; Bilibili has grown income through AI ads. Smaller companies also want to copy these paths, but they do not have enough users to build successful AI products. They can copy the form, but not the people, technology, and money behind it.

The AI industry also changes very fast. First came large models, then AI search and chat, now AI assistants and AI tools. At each stage, big companies move ahead first. There is an even bigger change: in the mobile phone era, small companies could build a special app for one group of users. Now big companies want one main "entry point"—users can ask questions, watch video, and listen to music in one AI. If that happens, users may no longer need to open many small apps. That is what smaller companies fear most.

Overall, smaller companies are not unaware that AI matters, and they have not done nothing. But in money, users, technology, and speed of change, they are falling further behind. Big and mid-size companies have some successful approaches, but smaller ones struggle to copy them fully. To change, they cannot only talk about AI—they need to truly change the company's direction.

In one sentence: rich big companies are running faster in the AI era; smaller firms are also working on AI, but lack money and cannot keep up with rapid change, so it is hard to earn new money from AI and their room to grow may keep shrinking.