Guidelines for AI and Art Authentication

Last Updated: November 14, 2025

This resource is intended to be for educational purposes only and does not offer legal advice. Readers who require advice on preparing and using AI systems in their work should consult an attorney in the appropriate jurisdiction.
Please note that Guidelines are subject to updates and changes.

Proliferation of artificial intelligence tools and models and the rise of AI tools in art authentication, prompted formation of the following framework for responsible use of AI in Art Authentication. Proposed as best practices guidelines, the following builds on four foundational principles: transparency, accountability, scientific rigor, and human-AI collaboration. This framework addresses both the technical development of AI systems and their practical adoption by art market participants, scholars, and cultural institutions. By requiring developers to disclose methodologies and training data in accessible language while demanding active collaboration with art experts throughout the AI lifecycle, the framework ensures that computational capabilities enhance rather than disrupt established authentication practices. Designed to be dynamic and adaptive, it evolves alongside technological innovation, legal developments, and academic research, ultimately aiming to safeguard artistic legacies, scholarly integrity, and cultural heritage while leveraging AI’s ability to detect patterns and process vast datasets in support of attribution decisions.

The Guidelines are Accessible HERE.

The Guidelines promote:

Enhanced Authentication Methods

Clear Communication

Informed and Enhanced Expert Collaboration

Ethical Integration

The foundational principles of transparency, scientific rigor, ethical responsibility, and human-AI collaboration must guide both the development of robust AI authentication models and the responsible, well-informed integration of AI into art authentication practices.

Carina Popovici, Art Recognition

However easy or difficult authentication of a particular work of art might be, having more high quality tools in the arsenal cannot hurt. The so-called three legged chair of art authentication that relies on scientific analysis, provenance research and connoisseurship now has an extra point of support – AI-systems.

Irina Tarsis, Center for Art Law

AI image analysis can be the art historian, art collector, and art market’s best friend, provided that the analysis is handled in a grownup, transparent, deeply-considered, professional manner. These guidelines represent best practice for this important new field, and following them will ensure that AI image analysis remains a trusted additional tool for art experts to use alongside traditional methods, like connoisseurship, provenance research, and material forensics.