The ALA Core Metadata Interest Group (MIG) invites proposals for two presentations for our program at the ALA Annual Conference 2026.
Program Title: AI-Assisted Metadata Creation: Real World Applications, Ethical Questions, and Practical Lessons
This session will explore how metadata professionals are applying artificial intelligence (AI) tools in real-word settings, highlighting both the potential and challenges of AI-assisted metadata creation.
As generative AI tools become more accessible, metadata professionals are beginning to explore its use in both MARC and non-MARC environments. From automated subject analysis and entity identification to transcription, captioning, and image description, AI tools are reshaping how libraries approach metadata creation, offering new efficiencies as well as new complexities.
This session will feature two presentations offering complementary perspectives:
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Presentation 1: focused on AI applications in MARC metadata environments
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Presentation 2: focused on AI applications in non-MARC metadata environments (e.g., digital libraries, archives, or institutional repositories)
Speakers are encouraged to share specific use cases or experiments from their institutional contexts, including but not limited to:
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Automating or enhancing cataloging and description tasks
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Using AI for accessibility (e.g. transcription, captioning, or image description)
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Entity identification or name disambiguation
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Workflow efficiencies and challenges (staffing, training or quality control)
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Data provenance, ethical implications, and transparency in AI outputs
Each speaker will have 20 minutes to present, followed by an audience Q&A. Submissions from all institution types are welcome. ALA Core membership is not required to present at or attend ALA Core programming.
If you are interested in sharing your work, or know someone doing innovative or experimental work with AI in metadata, please submit a brief proposal here by December 5, 2025, or share with colleagues who may be interested.
On behalf of the ALA Core Metadata Interest Group,
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Amber Jones
Metadata Librarian
Virginia Commonwealth University
She/Her/Hers
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