AI systems succeed or fail based on data quality, yet most enterprises use AI output without verifying underlying data .  Walrus positions itself as the trust layer for the data economy by providing cryptographic proof of data provenance and granular access controls.  In Walrus, every dataset has an on‑chain identity and verifiable history; users can prove where data came from and what changes occurred .  This is critical in an AI landscape where less than 20 % of AI outputs are reviewed before use .  Walrus goes further by enabling secure multi‑party computation: multiple parties can perform computations on confidential data and publish certified results .  These capabilities give rise to new data marketplaces where users, researchers and companies can monetise information with confidence .  Projects like CUDIS (health data sovereignty), Alkimi (AdFi) and Baselight (permissionless data marketplace) already demonstrate how trusted data unlocks innovation .  For AI builders, it means access to clean datasets; for enterprises, it means a way to buy and sell data without fearing manipulation.



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