Share and intensity of work current AI systems can materially affect.
SOC 25-4011
Archivists AI displacement risk
AI classification and OCR automate description and digitization workflows that used to consume archivist hours. Provenance judgment, appraisal of what to keep, authentication, and access policy keep the profession's judgment layer intact.
Likely potential for exposed tasks to move to software after workflow integration.
Digitization shifts archivist work from handling paper to governing digital collections — more material preserved, more need for someone who decides what matters and guarantees its authenticity. Description automates; appraisal does not.
Distribution
Where Archivists sits across 620 tracked roles
Displacement pressure 46 — higher than 76% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-08. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
13 O*NET task statements matched to SOC 25-4011. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $64,550 (May 2025, US national). The latest BLS row matched SOC 25-4011.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Archivists
SOC 25-4011 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 46/100 role score and are not an occupation forecast.
+0.4% group wage
-0.5% cognitive employment since mid-2026; 2.9% cognitive unemployment.
Economy-wide: +1.6% GDP and 3.9% unemployment.
-0.3% group wage
-3.9% cognitive employment since mid-2026; 4.5% cognitive unemployment.
Economy-wide: +8.3% GDP and 4.6% unemployment.
-11.5% group wage
-21.5% cognitive employment since mid-2026; 17.9% cognitive unemployment.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Archivists
The current evidence import matched 13 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks13
SOC25-4011
- Core task / ID 7631
Organize archival records and develop classification systems to facilitate access to archival materials.
- Core task / ID 7633
Provide reference services and assistance for users needing archival materials.
- Core task / ID 7635
Prepare archival records, such as document descriptions, to allow easy access to information.
- Core task / ID 7630
Create and maintain accessible, retrievable computer archives and databases, incorporating current advances in electronic information storage technology.
- Core task / ID 7637
Establish and administer policy guidelines concerning public access and use of materials.
- Core task / ID 7634
Direct activities of workers who assist in arranging, cataloguing, exhibiting, and maintaining collections of valuable materials.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Organize records and classification systems
Exposure 64, automation 38%, augmentation 66%.
O*NET evidence: Organize archival records and develop classification systems to facilitate access to ar... (ID 7631)
Prepare document descriptions
Exposure 72, automation 44%, augmentation 70%.
O*NET evidence: Prepare archival records, such as document descriptions, to allow easy access to inform... (ID 7635)
Preserve records in digital formats
Exposure 52, automation 28%, augmentation 62%.
O*NET evidence: Preserve records, documents, and objects, copying records to film, videotape, audiotape... (ID 7636)
Authenticate and appraise materials
Exposure 30, automation 10%, augmentation 52%.
O*NET evidence: Authenticate and appraise historical documents and archival materials. (ID 7632)
TaskExposureAutomationAugmentation
Organize records and classification systems6438%66%
Prepare document descriptions7244%70%
Preserve records in digital formats5228%62%
Authenticate and appraise materials3010%52%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
ModerateDigital Collections Manager
Training horizon: 3-6 months. Skill overlap 74. Wage preservation signal 112.
- Own digitization pipelines
- Set metadata standards
- Audit AI-generated descriptions
industry switch
ModerateRecords and Information Governance Analyst
Training horizon: 3-6 months. Skill overlap 62. Wage preservation signal 122.
- Learn retention schedule law
- Map corporate records flows
- Build compliance checklists
Comparison guides
Compare the next move before you commit
3-6 months
Archivists to Digital Collections Manager
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Archivists into Digital Collections Manager.
3-6 months
Archivists to Records and Information Governance Analyst
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Archivists into Records and Information Governance Analyst.
What the AI risk score means for Archivists
The displacement pressure score for Archivists is 46. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Prepare document descriptions carries 44% automation pressure, while Prepare document descriptions carries 70% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $64,550 (May 2025, US national). Employment context: Records preservation profession adapting to digital collections. Typical education: Master's degree in library or archival science typical.
Wage vulnerability is 44, while transition feasibility is 68. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Moderate displacement pressure
- Description work automates
- Appraisal and provenance persist
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Archivists, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Collection management
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Preservation methods
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Research
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Documentation
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Digital Collections Manager, such as own digitization pipelines.
- By 90 days, compare internal openings and external postings for Digital Collections Manager or Records and Information Governance Analyst and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Archivists
Will AI replace Archivists?
AI classification and OCR automate description and digitization workflows that used to consume archivist hours. Provenance judgment, appraisal of what to keep, authentication, and access policy keep the profession's judgment layer intact. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Archivists work are most exposed to AI?
Prepare document descriptions and Organize records and classification systems show the strongest automation pressure in this model. Prepare document descriptions and Organize records and classification systems are better treated as AI-augmented work.
What should Archivists learn next?
Start with Collection management, Preservation methods, Research. The most practical adjacent paths in this model are Digital Collections Manager and Records and Information Governance Analyst.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
International Labour Organization / 20 May 2025Generative AI and Jobs: A Refined Global Index of Occupational ExposureOECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics