NFTs were once treated as the symbol of digital art. Their mechanism of proving “uniqueness” seemed like a fresh counterbalance to the infinite reproducibility of digital data. The idea that the proof of existence itself could hold value, rather than the artwork alone, was indeed revolutionary.
However, NFTs were quickly consumed by commercial frenzy. The market expanded without a real understanding of the underlying concept, and countless pieces of digital waste were created. Detached from the artistic context, endless collections were generated and forgotten. That phenomenon reflected not the flaw of the technology itself, but the fragility of human desire driven by trends.
Perhaps the era simply arrived too early. Yet now, with the rise of generative AI, the situation feels different. Images, voices, and videos are produced from minimal prompts, and distinguishing authenticity has become increasingly difficult. In this age where the boundary between the real and the synthetic is fading, the need to verify who created what, and when, is once again growing.
AI-generated content is closer to a generation log than a traditional work of authorship. To trace its countless derivatives, to record their origins and transformations, we need a new system—and the foundational structure of NFTs fits naturally there. Immutable verification, decentralized ownership, traceable history. These can be redefined not as artistic features, but as mechanisms for ensuring information reliability.
Watching models like Sora 2 makes that necessity clear. When generated outputs become so real that human-made and AI-made works are indistinguishable, society begins to search again for a sense of uniqueness—not in aesthetic terms, but in informational and social terms. NFTs may quietly return, not as speculative art tokens, but as the infrastructure of provenance and trust.
The meaning of a technology always changes with its context. NFTs did not end as a mere symbol of the bubble. They might have been the first structural answer to the question that defines the AI era: what does it mean for something to be genuine? Now may be the time to revisit that architecture and see it anew.