BLOCKCHAIN AND AI IN ART PROVENANCE TRACKING
DOI:
https://doi.org/10.29121/shodhkosh.v7.i1s.2026.7119Keywords:
Artificial Intelligence, Blockchain, Art Provenance, Artwork Authentication, Cultural Heritage, Digital Art MarketsAbstract [English]
The increased digitization of the art market around the world has contributed to an enhanced demand to have dependable, transparent and tamper-proof provenance tracking systems. The conventional provenance records, which are usually sporadic, are handled by humans and institution-specific, are susceptible to forgery, loss of data, and deliberate alteration. The solution to these issues in art provenance tracking is the proposed framework in this paper that integrates Artificial Intelligence (AI) and Blockchain technologies to enhance provenance tracking. Digitized artworks using AI methods can be analyzed to produce high-level visual, material and stylistic features which can be used to assess the authenticity of artworks automatically, detect anomalies, and analyze similarities between works across large collections of art. At the same time, the Blockchain technology offers a decentralized and unchangeable registry to securely store provenance events including ownership changes, restoration histories, exhibition histories, and artificial intelligence generated authenticity scores. The suggested structure provides a smooth flow of work where AI-generated metadata and the confidence measures are hashed via hashing algorithms and anchored to the Blockchain which ensures the integrity of data, transparency, and the long-term traceability. The methodology includes the process of digitizing artwork, standardizing metadata, training models to analyze the visual data, and considerations of the Blockchain network design i.e. consensus mechanism and smart contracts. This has been demonstrated by experimental evaluation that the integrated approach greatly increases provenance reliability, decreases the effort of manual verification, and increases trust between artists, collectors, galleries, and cultural institutions. The paper critically evaluates the issues of data bias in AI models, scalability and power consumption in Blockchain systems, legal and ethical restrictions on digital ownership and privacy as well.
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Copyright (c) 2026 Dr. Gajanan P Arsalwad, Faldu Poonam R, Karuna S Bhosale, Akshay Hemant Gongane, Shalini E, Om Prakash
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