AI's application in marketing is rapidly expanding, and "AI customer acquisition" is one of the most closely watched directions. For enterprises, it does reduce the cost of content production; for the information environment, it also brings new problems. These two things need to be discussed separately.
Efficiency gains on the enterprise side are real
AI can generate copy, images, and even videos in bulk in a very short time, so content output no longer depends on team size. In the placement and distribution stages, algorithms can also be used for more precise matching. From a cost perspective, this is a clear improvement.
The problem emerges after this capability becomes widely used. When all participants can produce content at low cost, the differentiation of the content itself declines, and frequency of appearance replaces content quality as the main factor affecting visibility. The result is that the party investing more gains a greater share of voice, even if its content is not more valuable.
The cost of discernment on the user side is rising
For ordinary users, distinguishing genuine reviews from generated content is becoming increasingly difficult. Generative optimization technology can make brand information appear in answers in the form of "objective recommendations," which makes the credibility of recommendations hard to judge.
When users find that the "high cost-performance" information they retrieve does not actually hold up, what is damaged is not only trust in a particular brand, but trust in the entire source of information. Once this kind of loss takes shape, it is very slow to recover.
The practical impact on enterprises
Here is an easily overlooked consequence: when low-quality content occupies a large share of exposure slots, enterprises that earnestly make products and provide services become harder to see. They often do not have advertising budgets of the same scale, so they are at a disadvantage in this mechanism that judges by share of voice.
This is also why "content verifiability" has become more important. When information supply is excessive, the value of content that can be verified and traced to a clear source rises relatively. Official websites, qualifications, case studies, and verifiable data once again become the basis for customers' judgment.
A pragmatic judgment
AI holds up as an efficiency tool, and using it to reduce the cost of repetitive content work is itself uncontroversial. But placing "being seen" entirely on bulk generation and ad placement may work in the short term, while in the long term it will drag enterprises into a competition with ever-rising costs.
A more sustainable approach is to use AI in the efficiency link of content production, while putting the accuracy and verifiability of content first. Recommendations can take frequency into account, but decisions ultimately have to return to facts.