Looking back from the perspective of 2026, the explosive growth of AI agents is reshaping the entire data storage landscape.

Most people talk about AI by focusing on GPU computing power and large model parameters, but they overlook a critical shortcoming—data storage. As new generation models like GPT-6 and Claude 4 emerge, AI is no longer just simple dialogue boxes but has evolved into truly autonomous intelligent agents. These agents need to process massive amounts of unstructured data, including training corpora, interaction histories, and real-time contextual memory.

The question is. How big are the pitfalls of existing storage solutions?

First, centralization risk. Your decentralized AI model data stored on AWS can be shut down or deleted at Amazon’s will. For Web3AI that claims to resist censorship, this is simply unacceptable. Second, cost runaway. When multimodal data like videos and 3D models explode, the bandwidth costs of traditional cloud storage soar straight up.

That’s why storage protocols based on the Sui network are beginning to emerge. Through their unique architectural design, they aim to become a truly decentralized memory bank in the AI era, while strategically positioning themselves in the DePIN track.