Summary of Key Points
This article highlights a common misconception about the current use of AI by discussing a conversation with a trade boss. People often focus too much on the potential of AI to reduce costs and increase efficiency—such as saving time or replacing jobs—but the real goal for businesses is to use AI to generate revenue, not just to cut expenses. The article introduces the concept of “AI-native companies,” which are not those that simply add AI tools to existing businesses; instead, they start from the fundamentals of AI to redesign their organizational structures, processes, and customer acquisition methods, even creating new business models that were previously unattainable. It also highlights the differences in thinking between technologists and businessmen, as well as the practical approach to building AI-native companies (first proving the concept within the company before commercializing it), emphasizing that the ultimate value of AI is to reinvent business models, not just to optimize existing processes.
Detailed Analysis
1. “Don’t Tell Bosses About Saving People; They Only Care About Making More Money”
The daily concerns of business owners are not about whether they can hire one fewer editor, but about where their orders come from, why customers choose them, how to manage inventory, and when they will get paid. When discussing AI, the focus is often on cost reduction and efficiency improvements (such as writing 20 marketing pieces in a day or editing a video in minutes), but these are indicators of efficiency, not actual business outcomes. If 30 AI-generated videos don’t bring in a single customer, then high efficiency is meaningless. While there is a limit to cost reduction (for example, a department might reduce costs to zero), there is no limit to growth. Business owners would prefer to spend 100,000 on AI that can increase sales by 1 million rather than on a tool that saves 150,000 in costs, because making money is the lifeblood of a business.
2. “AI-Native Companies: Not ‘Adding AI Plugins to Old Companies,’ but ‘Building Companies from the Ground Up with AI’”
When the internet first emerged, many companies just added a website (a combination of a traditional business and the internet), but it was platforms like Taobao that truly transformed the industry by redefining transactions using internet logic. The same is true for AI-native companies:
- It’s not about using AI to have the marketing department write copy; instead, the question is, “Does the marketing department really need that many people?”
- It’s not about using AI robots for customer service; rather, the question is, “Do we still need a separate customer service department?”
- It’s not about using AI to assist in sales follow-ups; instead, the question is, “Do we still need to individually pursue each customer?”
The trade boss in the article wants to use AI to redesign his customer acquisition, supply chain, and financial management strategies—basically, to restructure his entire business using AI.
3. The Different Thinking Approaches of Technologists and Businessmen
Technologists see AI in terms of potential replacements for jobs and automations (e.g., replacing customer service or editors), while businessmen see it as an opportunity to sell new products or access new markets. The outcome of these two approaches is completely different. Technologists focus on the functionality of the tools, while businessmen look for new business opportunities. Even if they don’t understand coding, those who understand the business can create new models of sales as long as they realize that AI can lower marginal costs (for example, making personalized products more affordable).
4. “How to Implement AI-Native Companies? Use Your Own Company as a Test Bed”
Many AI startups develop tools before looking for customers, but smart business owners do the opposite: they test AI solutions within their own company first. For instance, the trade boss tested AI for customer acquisition, marketing, and supply chain management, and once he saw significant results (such as a tripling of average sales per employee), he then turned these methods into systems for sale or used them to start a new company. This approach is much more persuasive than simply promoting a tool. A business owner might not be interested in hearing that “our AI can automatically follow up with 70% of customers,” but they will be very interested in learning that “our own trade company’s average sales per employee has tripled” after implementing AI.
5. “The Ultimate Value of AI: Not to Make Old Business Faster, but to Create New Business”
AI is not about making things faster (like a faster horse or an electronic newspaper); its real value lies in creating new business models that didn’t exist before:
- For small businesses that couldn’t afford professional marketing teams, AI can help with targeted customer acquisition.
- For products that were too expensive for personalized customization, AI can lower costs and meet demand more efficiently.
- For services that were unfeasible in remote areas, AI can provide low-cost solutions through intelligent systems.
In the future, it won’t be tools that help companies save employees that will transform business, but AI-native practices that demonstrate new ways of operating.
Final Conclusion
Businesses exist to make money, not to save money. The true value of AI is to help them find new ways to generate revenue, not to eliminate a few positions.
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