The conference system is undergoing a severely overlooked transformation. In the era of Web3, RWA, and AI-driven global collaboration, it is no longer just an information tool but is gradually evolving into a true data infrastructure. The core driving force behind this shift is actually AI—not blockchain.

Traditional conference systems accumulate data daily. Registration information, check-in records, attendee lists, interaction data—piling up. But the problem is that these data are long locked in the "record layer," severely fragmented, lacking semantic understanding, and unable to connect across meetings. Without intelligent analysis, these data are almost impossible to flow to the actual decision-making level. In other words, the data is like gold lying in a warehouse—no one can truly utilize it.

AI is not changing the quantity of data but its value structure. Once AI intervenes, conference data will experience three levels of leap:

**First level**: Upgrading from "who came" to understanding behavior itself. The system begins to identify frequent participants, key collaborators, and true decision-makers, forming traceable behavior trajectories for each participant.

**Second level**: Evolving from isolated single-meeting data to continuous participation networks. Recognizing participation patterns, professional backgrounds, and potential collaboration opportunities, enabling long-term reuse of data. Participants are no longer just "attended once," but are fully recorded in the collaboration map.

**Third level**: Shifting from passive information display to proactive decision support. Influencing activity design, collaboration matching, and project implementation from the back end. Data begins to truly guide operations.

In this way, the conference system has fundamentally transformed. For organizations, it shifts from gut-feeling judgments to data-driven collaborative decision-making; for individuals, participation is no longer a one-time act but a record of verifiable, computable identities; for the entire ecosystem, conference data no longer constructs just a list of events but a real collaboration network.

The true bottleneck of Web3 and RWA has never been technology but trust—how to establish it, how to sustain collaboration, and how to reuse participation. The significance of expanding conference data through AI lies in making "participation" the first time a computable, reusable, and predictable digital asset.

The future winners will not be those who host the most events but those who possess the most, and most authentic, AI-understandable participation data. When conference data meets AI, what happens is not just efficiency improvement but a complete reorganization of organizational logic—events start to have memory, participation begins to accumulate, and collaboration gains predictive capabilities. This is the true operational foundation of the next-generation Web3 organizations and RWA projects.