Share and intensity of work current AI systems can materially affect.
SOC 25-1011
Business Teachers, Postsecondary AI displacement risk
Business faculty teach finance, marketing, and operations while employers demand graduates who can manage AI tools, forcing the fastest curriculum redesign in the university. Case-method discussion, practitioner networks, and research credibility keep faculty central; lecture-drafting and grading compress first.
Likely potential for exposed tasks to move to software after workflow integration.
The case method survives because it teaches judgment under ambiguity, not information recall. Faculty who rebuild courses around AI-assisted analysis teach what employers are actually hiring for; those who only lecture from slides face recorded-content competition.
Distribution
Where Business Teachers, Postsecondary sits across 620 tracked roles
Displacement pressure 32 — higher than 52% 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.
25 O*NET task statements matched to SOC 25-1011. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $99,080 (May 2025, US national). The latest BLS row matched SOC 25-1011.
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 Business Teachers, Postsecondary
SOC 25-1011 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 32/100 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 Business Teachers, Postsecondary
The current evidence import matched 25 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 tasks25
SOC25-1011
- Core task / ID 5662
Prepare and deliver lectures to undergraduate or graduate students on topics such as financial accounting, principles of marketing, and operations management.
- Core task / ID 5663
Evaluate and grade students' class work, assignments, and papers.
- Core task / ID 5667
Initiate, facilitate, and moderate classroom discussions.
- Core task / ID 5665
Prepare course materials, such as syllabi, homework assignments, and handouts.
- Core task / ID 5670
Keep abreast of developments in the field by reading current literature, talking with colleagues, and participating in professional organizations and conferences.
- Core task / ID 5668
Plan, evaluate, and revise curricula, course content, and course materials and methods of instruction.
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 lectures on business topics
Exposure 56, automation 28%, augmentation 72%.
O*NET evidence: Prepare and deliver lectures to undergraduate or graduate students on topics such as fi... (ID 5662)
Evaluate and grade student work
Exposure 54, automation 30%, augmentation 64%.
O*NET evidence: Evaluate and grade students' class work, assignments, and papers. (ID 5663)
Plan and revise curricula and course materials
Exposure 52, automation 26%, augmentation 68%.
O*NET evidence: Plan, evaluate, and revise curricula, course content, and course materials and methods ... (ID 5668)
Advise students on academic and career issues
Exposure 26, automation 8%, augmentation 48%.
O*NET evidence: Advise students on academic and vocational curricula and career issues. (ID 5671)
TaskExposureAutomationAugmentation
Prepare and deliver lectures on business topics5628%72%
Evaluate and grade student work5430%64%
Plan and revise curricula and course materials5226%68%
Advise students on academic and career issues268%48%
Transition pathways
Adjacent moves that preserve existing skills
credentialed transition
ModerateDepartment Chair
Training horizon: 12-24 months. Skill overlap 66. Wage preservation signal 116.
- Lead curriculum redesign
- Manage faculty hiring
- Own program outcomes
role redesign
ModerateExecutive Education Director
Training horizon: 6-12 months. Skill overlap 70. Wage preservation signal 118.
- Sell corporate programs
- Build AI-fluency curricula
- Manage practitioner faculty
Comparison guides
Compare the next move before you commit
12-24 months
Business Teachers, Postsecondary to Department Chair
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Business Teachers, Postsecondary into Department Chair.
6-12 months
Business Teachers, Postsecondary to Executive Education Director
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Business Teachers, Postsecondary into Executive Education Director.
What the AI risk score means for Business Teachers, Postsecondary
The displacement pressure score for Business Teachers, Postsecondary is 32. 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 lectures on business topics carries 72% 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: $99,080 (May 2025, US national). Employment context: Faculty role racing the AI-native curriculum. Typical education: Doctoral degree typical.
Wage vulnerability is 30, while transition feasibility is 71. 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
- AI-native curriculum demand is rising
- Case discussion resists recording
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Business 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.
Business 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.
Curriculum 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.
Case facilitation
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.
Career advising
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 Executive Education Director and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Business Teachers, Postsecondary
Will AI replace Business Teachers, Postsecondary?
Business faculty teach finance, marketing, and operations while employers demand graduates who can manage AI tools, forcing the fastest curriculum redesign in the university. Case-method discussion, practitioner networks, and research credibility keep faculty central; lecture-drafting and grading compress first. 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 Business Teachers, Postsecondary work are most exposed to AI?
Evaluate and grade student work and Prepare and deliver lectures on business topics show the strongest automation pressure in this model. Prepare and deliver lectures on business topics and Plan and revise curricula and course materials are better treated as AI-augmented work.
What should Business Teachers, Postsecondary learn next?
Start with Business instruction, Curriculum design, Case facilitation. The most practical adjacent paths in this model are Department Chair and Executive Education 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