Share and intensity of work current AI systems can materially affect.
SOC 25-4022
Librarians and Media Collections Specialists AI displacement risk
Search and retrieval — once the heart of reference work — is exactly what AI now does instantly. Collection curation, information literacy instruction, community programming, and guidance on evaluating AI-era information quality keep librarians relevant.
Likely potential for exposed tasks to move to software after workflow integration.
Reference-question volume declines as AI answers spread, but demand for teaching people to verify, cite, and critically evaluate information is rising. Community anchoring matters more than retrieval speed.
Distribution
Where Librarians and Media Collections Specialists sits across 620 tracked roles
Displacement pressure 42 — higher than 70% 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.
30 O*NET task statements matched to SOC 25-4022. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $68,270 (May 2025, US national). The latest BLS row matched SOC 25-4022.
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 Librarians and Media Collections Specialists
SOC 25-4022 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 42/100 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 Librarians and Media Collections Specialists
The current evidence import matched 30 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 tasks30
SOC25-4022
- Core task / ID 22411
Search standard reference materials, including online sources and the Internet, to answer patrons' reference questions.
- Core task / ID 22412
Analyze patrons' requests to determine needed information and assist in furnishing or locating that information.
- Core task / ID 22413
Supervise daily library operations, budgeting, planning, and personnel activities, such as hiring, training, scheduling, and performance evaluations.
- Core task / ID 22414
Plan and teach classes on topics such as information literacy, library instruction, and technology use.
- Core task / ID 22416
Code, classify, and catalog books, publications, films, audio-visual aids, and other library materials, based on subject matter or standard library classification systems.
- Core task / ID 22415
Confer with colleagues, faculty, and community members and organizations to conduct informational programs, make collection decisions, and determine library services to offer.
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
Answer reference questions
Exposure 74, automation 46%, augmentation 62%.
O*NET evidence: Search standard reference materials, including online sources and the Internet, to answ... (ID 22411)
Catalog and classify materials
Exposure 68, automation 42%, augmentation 54%.
O*NET evidence: Code, classify, and catalog books, publications, films, audio-visual aids, and other li... (ID 22416)
Teach information literacy
Exposure 38, automation 12%, augmentation 52%.
O*NET evidence: Plan and teach classes on topics such as information literacy, library instruction, and... (ID 22414)
Plan community programs
Exposure 30, automation 8%, augmentation 42%.
O*NET evidence: Confer with colleagues, faculty, and community members and organizations to conduct inf... (ID 22415)
TaskExposureAutomationAugmentation
Answer reference questions7446%62%
Catalog and classify materials6842%54%
Teach information literacy3812%52%
Plan community programs308%42%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
ModerateDigital Literacy Program Manager
Training horizon: 2-5 months. Skill overlap 74. Wage preservation signal 104.
- Design AI literacy curriculum
- Measure program outcomes
- Partner with schools and employers
industry switch
ModerateKnowledge Management Specialist
Training horizon: 3-6 months. Skill overlap 66. Wage preservation signal 124.
- Organize internal knowledge bases
- Set content governance rules
- Evaluate retrieval AI tools
Comparison guides
Compare the next move before you commit
2-5 months
Librarians and Media Collections Specialists to Digital Literacy Program Manager
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Librarians and Media Collections Specialists into Digital Literacy Program Manager.
3-6 months
Librarians and Media Collections Specialists to Knowledge Management Specialist
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Librarians and Media Collections Specialists into Knowledge Management Specialist.
What the AI risk score means for Librarians and Media Collections Specialists
The displacement pressure score for Librarians and Media Collections Specialists is 42. 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. Answer reference questions carries 46% automation pressure, while Answer reference questions carries 62% 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: $68,270 (May 2025, US national). Employment context: Public-service information role reinventing around digital literacy. Typical education: Master's degree in library science typical.
Wage vulnerability is 44, while transition feasibility is 70. 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
- Retrieval work is automating
- Information literacy demand is rising
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Librarians and Media Collections Specialists, 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.
Information evaluation
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.
Collection curation
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.
Instruction
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.
Community programming
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 Literacy Program Manager, such as design ai literacy curriculum.
- By 90 days, compare internal openings and external postings for Digital Literacy Program Manager or Knowledge Management Specialist and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Librarians and Media Collections Specialists
Will AI replace Librarians and Media Collections Specialists?
Search and retrieval — once the heart of reference work — is exactly what AI now does instantly. Collection curation, information literacy instruction, community programming, and guidance on evaluating AI-era information quality keep librarians relevant. 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 Librarians and Media Collections Specialists work are most exposed to AI?
Answer reference questions and Catalog and classify materials show the strongest automation pressure in this model. Answer reference questions and Catalog and classify materials are better treated as AI-augmented work.
What should Librarians and Media Collections Specialists learn next?
Start with Information evaluation, Collection curation, Instruction. The most practical adjacent paths in this model are Digital Literacy Program Manager and Knowledge Management Specialist.
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