AI is already transcribing handwritten documents, generating metadata, and identifying items in image collections. Here's what that means for your career and what to do about it.
AI won't replace archivists, but it's already replacing some of the tedious work archivists do. Description backlogs are shrinking as machine learning tools auto-tag photos and transcribe manuscripts. Appraisal judgment, community trust, and ethical stewardship remain irreplaceable.
TASK LEVEL RISK
Most of the work stays human. AI assists at the edges.
AI is handling specific tasks. The core role is intact but shifting.
AI is automating significant portions of the work. Adaptation is essential.
Higher risk
handwritten text transcription, basic metadata generation, image tagging, OCR of typed documents, keyword indexing, format migration checks, duplicate detection
Lower risk
appraisal decisions, donor negotiations, cultural sensitivity reviews, provenance research, restricted access rulings, exhibit curation, reference interviews
Archival work depends on appraisal judgment, cultural sensitivity, and accountability to donors and communities that AI systems cannot ethically assume.
WHAT YOU SHOULD DO
Skills to build for the AI era
New skills - Adapt to the AI landscape
New skills - Adapt to the AI landscape
Use handwritten text recognition and machine learning tools like Transkribus to accelerate transcription and metadata generation across large collections.
Manage born-digital records using tools like BitCurator and Archivematica, ensuring long-term access despite format obsolescence and media decay.
Publish archival descriptions using RDF, Wikidata, and authority linking to make collections discoverable across the semantic web.
Evaluate AI-generated metadata for bias, accuracy, and cultural harm before applying it to descriptive records or public interfaces.
Timeless skills - What AI can't replicate
Timeless skills - What AI can't replicate
Decide which records have enduring value based on institutional mission, historical context, and anticipated research use over generations.
Build trust with individuals and organizations transferring papers, negotiating access restrictions and rights with empathy and professional discretion.
Balance access, privacy, and cultural sensitivity when handling records about marginalized communities, sensitive events, or living individuals.
THE FULL PICTURE
What AI can do, what it can't, and where the career is headed
What AI can already do
- Transcribe handwritten historical documents using HTR tools
- Generate descriptive metadata for large image collections
- Identify duplicate or near-duplicate records across repositories
- Extract entities like names and places from digitized text
- Flag potential preservation risks in digital file formats
- Suggest subject headings based on document content
What AI can't do
- AI cannot decide which records have enduring historical value for future generations.
- AI cannot navigate ethical questions about restricting access to sensitive community records.
- AI cannot build trusting relationships with donors negotiating personal or institutional papers.
- AI cannot interpret cultural context that shapes how materials should be described or shared.
- These are the core contributions of Archivists, and they remain entirely human.
Archivists who embrace AI as a description accelerator while deepening their appraisal and community expertise will define the profession's next decade.
Do you have the right strengths for this career?
Our test measures your personality and strengths — and shows how you match with 1600+ careers.
Job outlook
The Bureau of Labor Statistics projects employment of archivists, curators, and museum workers to grow 10 percent from 2024 to 2034, faster than average. Demand is strongest at universities, government archives, and cultural heritage institutions expanding digital collections. Specialists in digital preservation, born-digital records, and community archives have the best prospects.