Summary of the Core Concept in One Sentence
This article introduces a highly counterintuitive new concept called “efficiency inflation”: Just as inflation makes money less valuable over time, the widespread adoption of AI will lead to a simultaneous increase in everyone’s efficiency. What used to be a source of substantial profits—high efficiency—will soon become the new baseline for the industry. As a result, people will work more and faster, but without experiencing any real relief or additional earnings. The real solution lies not in continuously striving for higher efficiency; rather, it’s about using AI to pursue entirely new business opportunities that were previously too costly or unfeasible, thereby breaking away from the old competitive landscape.
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Plain-Language Explanation of the Key Points
1. What is “efficiency inflation”? Simply put, it means that efficiency can become as depreciated in value as money.
We all understand inflation: 20 years ago, 100 yuan could buy 50 pounds of rice; now, it can only buy 10 pounds. This isn’t because there’s less rice, but because everyone has more money, reducing its purchasing power. Efficiency inflation follows the same logic. If you were a salesperson 10 years ago and could meet three clients a day, outperforming your peers, you’d have a real competitive advantage and earn more commissions. But with AI helping you automate customer background checks and draft follow-up messages, you might meet 30 clients a day. However, if everyone in the industry uses the same AI, meeting 30 clients won’t be a competitive advantage anymore; it’ll just become a new KPI for your company. If you don’t meet the target, you might get criticized for being lazy. Even though your output value has increased tenfold, your commissions might not increase, and clients might even expect you to respond instantly. In other words, the value of your “efficiency” has depreciated, just like money in an inflationary environment.
2. Why do companies earn less money despite increased efficiency from AI? The problem lies in the unchanged “relative rankings.”
The article uses the college entrance exam as a clear example: Suppose 100 students are admitted to top universities each year. 30 years ago, without extra tutoring or online resources, a score of 650 was enough; now, with AI and personalized learning, the minimum score has risen to 700. But the number of admissions remains the same. Even if you put in three times the effort and use advanced technologies, you might end up with the same number of admissions as someone who scored 650 back then. For companies, if the entire industry uses AI to reduce costs by 30%, and competitors also lower their prices by 30%, consumers get all the benefits of the reduced costs, leaving you with a 30% reduction in profits. Technology can boost everyone’s capabilities, but if the number of top positions doesn’t increase, the competition will only raise the bar, leaving no one with extra gains.
3. The most hidden trap of efficiency inflation: It turns “overtime” into “normal work.”
Many people think AI will free up time, allowing them to leave work earlier. However, this is wishful thinking. Over the years, technology has only increased the workload. In the past, you could leave the office and expect no calls or messages after hours; now, with smartphones and messaging apps, not responding immediately can be seen as a problem. AI will only exacerbate this trend, turning saved time into more work. For example, a research report that used to take 7 days can now be completed in half a day, but your boss will still expect you to produce multiple reports in a single day. All the extra time saved by technology is absorbed by the increased workload.
4. 90% of companies using AI are essentially digging their own graves.
When you ask business owners what they plan to do with AI, most will say things like hiring fewer employees, cutting unnecessary staff, or making existing tasks more efficient. For instance, tasks that previously required five programmers can now be done by two, or public account posts that used to take a week can now be produced daily. Essentially, everyone gets a “fast car” but uses it on the same old, crowded roads, leading to increased competition and harder work. Using AI to do things faster doesn’t necessarily result in more customers or higher profits; instead, it just raises the bar for everyone.
5. The real solution is to create new, uncharted opportunities.
Since competing on efficiency in the old ways only leads to more exhaustion, the real breakthrough is to use AI to pursue new, untested business models. For example, instead of making traditional services faster, use AI to develop entirely new services. Consider online tutoring: while it used to be expensive and unfeasible on a large scale, AI makes it affordable and creates a new market with huge potential. In the past, no one could increase their college entrance exam score from 650 to 700; with AI, you can create a new competition with no established rules. The true beneficiaries of AI are those who use it to create entirely new businesses, not just to improve efficiency.
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In summary, the article highlights how the widespread use of AI can lead to increased efficiency but not necessarily greater profits. The real challenge is to use AI to innovate and create new opportunities rather than just improve existing processes.