[THE VIEW]In the Age of AI, Competitiveness Lies in Seeing Things Differently

The Era of AI Standardization: Human Creativity Begins Anew
True Creation After Generation Belongs to People

Thanks to generative artificial intelligence (AI), we have entered an era where anyone can produce “plausible” content. Smooth sentences, stylish images, and logical proposals can all be generated with just a few lines of prompts. Tasks that once required expertise and significant time investment can now be completed quickly by anyone, regardless of their level of expertise. Ironically, however, as everyone begins to use the same tools, the value of well-crafted content is rapidly diminishing. We are now entering an age of generative standardization, where both creativity and differentiation are under threat.

Among investors in Silicon Valley, it is now common to hear remarks that startup presentations, pitch decks, and marketing plans all look as if they were created by generative AI. On the surface, they appear flawless: there are no spelling mistakes, and the logic is coherent. Yet, the structures and expressions feel overly familiar and repetitive. The unique perspective or sense of urgency of the founder is rarely felt. The quality of the content is no longer a competitive advantage. Everyone knows how to “make it well,” and AI delivers this faster than anyone else.

Recently, promotional content for startups, video descriptions by YouTube creators, advertising copy for major brands, and even job application self-introductions are being mass-produced through AI-based generative platforms. The expressions are polished and the sentences are well-organized, but the repetitive styles and structures make the content increasingly bland and indistinguishable. No matter how much of this content is produced, it leaves little impression. In fact, what truly resonates with people are the pieces that, even if imperfect, reveal the creator’s unique experiences and perspectives. Even if the delivery is somewhat clumsy, audiences recognize the genuine thought and sincerity behind it.

The core of this problem lies in how generative AI operates. Generative AI learns from massive datasets, absorbing the expressions and sentence patterns most frequently used in the past, and generates sentences in the most familiar and conventional forms. In other words, it selects words that are commonly used, sentence structures that are often connected, and expressions that are generally accepted. While this approach is stable and natural, it is fundamentally confined to familiarity. The expressions are smooth and the sentences are polished, but there is nothing unfamiliar or distinctive within them. In a world overflowing with well-made content, what stands out is what is made differently.

In an era where everyone can create content with AI, true competitiveness lies not in making it well but in 'seeing differently.' Image = Google Gemini

The creativity required in this era is different from the past. It is not simply the ability to quickly produce high-quality results, but rather the ability to ask different questions and view problems from a different perspective, even when using the same tools. In an age where generative AI delivers perfection, it is up to humans to provide differentiated interpretations and sensibilities. The way content unfolds, the interpretation of context, and the imperfect fluctuations of emotion are all elements of human creativity that AI struggles to imitate.

This shift is clearly visible in educational settings as well. Many university professors have fundamentally changed their methods of evaluating assignments since the advent of ChatGPT. They now focus more on the student’s sense of the problem and how they approached the assignment, as well as how they critiqued and restructured AI-generated content. To properly measure creativity, it is necessary to evaluate not just the finished product but the thought process behind it. Increasingly, instead of instructing students “not to use ChatGPT,” professors are asking them to explain “how they used it and where their own thinking began.”

In this context, the difference between those who use AI well and those who rely solely on AI will become increasingly clear. The former are those who can deconstruct and reconstruct AI-generated content, layering human intention and sensibility onto machine-generated sentences. The latter are those who are satisfied with the results produced by AI and use them as-is. While this difference may seem subtle on the surface, it ultimately creates a significant gap in reader response, consumer memory, and market choice.

Technology brings standardization. And when that standardization reaches its limit, the role of humans begins anew. What matters is not whether you used AI, but how you changed what AI created. In a world where everyone has the same tools, true competitiveness starts not with “what to make,” but with “how to see things differently.” And ultimately, that difference is created by people.

Professor Yoonseok Son, University of Notre Dame, USA