Share and intensity of work current AI systems can materially affect.
SOC 25-1042
Biological Science Teachers, Postsecondary AI displacement risk
Biology faculty teach molecular biology and botany while running research programs. AI tools now design experiments and annotate genomes, but the teaching laboratory — pipettes, cultures, dissections — is supervised physical instruction, and research at the bench still runs on trained hands.
Likely potential for exposed tasks to move to software after workflow integration.
Bioinformatics tooling compresses analysis time and raises research output per lab. Enrollment in pre-health tracks keeps teaching demand strong, and lab supervision cannot be streamed.
Distribution
Where Biological Science Teachers, Postsecondary sits across 620 tracked roles
Displacement pressure 26 — higher than 37% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
27 O*NET task statements matched to SOC 25-1042. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $84,620 (May 2025, US national). The latest BLS row matched SOC 25-1042.
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 Biological Science Teachers, Postsecondary
SOC 25-1042 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 26/100 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 Biological Science Teachers, Postsecondary
The current evidence import matched 27 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 tasks27
SOC25-1042
- Core task / ID 5800
Evaluate and grade students' class work, laboratory work, assignments, and papers.
- Core task / ID 5799
Prepare and deliver lectures to undergraduate or graduate students on topics such as molecular biology, marine biology, and botany.
- Core task / ID 5807
Plan, evaluate, and revise curricula, course content, and course materials and methods of instruction.
- Core task / ID 20061
Prepare materials for laboratory activities and course materials, such as syllabi, homework assignments, and handouts.
- Core task / ID 5806
Initiate, facilitate, and moderate classroom discussions.
- Core task / ID 5803
Supervise students' laboratory work.
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
Prepare and deliver biology lectures
Exposure 54, automation 27%, augmentation 70%.
O*NET evidence: Prepare and deliver lectures to undergraduate or graduate students on topics such as mo... (ID 5799)
Supervise student laboratory work
Exposure 24, automation 8%, augmentation 50%.
O*NET evidence: Supervise students' laboratory work. (ID 5803)
Evaluate and grade student work
Exposure 54, automation 30%, augmentation 62%.
O*NET evidence: Evaluate and grade students' class work, laboratory work, assignments, and papers. (ID 5800)
Keep abreast of developments in the field
Exposure 44, automation 22%, augmentation 62%.
O*NET evidence: Keep abreast of developments in the field by reading current literature, talking with c... (ID 5804)
TaskExposureAutomationAugmentation
Prepare and deliver biology lectures5427%70%
Supervise student laboratory work248%50%
Evaluate and grade student work5430%62%
Keep abreast of developments in the field4422%62%
Transition pathways
Adjacent moves that preserve existing skills
credentialed transition
LowDepartment Chair
Training horizon: 12-24 months. Skill overlap 64. Wage preservation signal 116.
- Lead curriculum redesign
- Manage research portfolios
- Own program outcomes
role redesign
LowCore Facility Director
Training horizon: 6-12 months. Skill overlap 66. Wage preservation signal 112.
- Run shared instrumentation labs
- Train facility users
- Manage grant recharges
Comparison guides
Compare the next move before you commit
12-24 months
Biological Science Teachers, Postsecondary to Department Chair
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Biological Science Teachers, Postsecondary into Department Chair.
6-12 months
Biological Science Teachers, Postsecondary to Core Facility Director
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Biological Science Teachers, Postsecondary into Core Facility Director.
What the AI risk score means for Biological Science Teachers, Postsecondary
The displacement pressure score for Biological Science Teachers, Postsecondary is 26. 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. Evaluate and grade student work carries 30% automation pressure, while Prepare and deliver biology lectures 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: $84,620 (May 2025, US national). Employment context: Faculty role anchored by the wet lab. Typical education: Doctoral degree typical.
Wage vulnerability is 30, 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.
- Low displacement pressure
- AI compresses analysis, not bench work
- Pre-health enrollment stays strong
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Biological Science Teachers, Postsecondary, 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.
Biology 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.
Laboratory supervision
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 mentoring
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.
Assessment design
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 Department Chair, such as lead curriculum redesign.
- By 90 days, compare internal openings and external postings for Department Chair or Core Facility Director and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Biological Science Teachers, Postsecondary
Will AI replace Biological Science Teachers, Postsecondary?
Biology faculty teach molecular biology and botany while running research programs. AI tools now design experiments and annotate genomes, but the teaching laboratory — pipettes, cultures, dissections — is supervised physical instruction, and research at the bench still runs on trained hands. 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 Biological Science Teachers, Postsecondary work are most exposed to AI?
Evaluate and grade student work and Prepare and deliver biology lectures show the strongest automation pressure in this model. Prepare and deliver biology lectures and Evaluate and grade student work are better treated as AI-augmented work.
What should Biological Science Teachers, Postsecondary learn next?
Start with Biology instruction, Laboratory supervision, Research mentoring. The most practical adjacent paths in this model are Department Chair and Core Facility Director.
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