Role Definition
| Field | Value |
|---|---|
| Job Title | Postsecondary Teachers, All Other (SOC 25-1199) |
| Seniority Level | Mid-to-Senior (Associate/Full Professor, Senior Lecturer, 5-15+ years) |
| Primary Function | Teaches courses at colleges and universities in subjects not separately classified by BLS — interdisciplinary programmes, emerging fields (digital humanities, sustainability, AI ethics), continuing education, professional development, and smaller academic departments. Conducts research, publishes in peer-reviewed journals, develops curricula, assesses student work, mentors students, and serves on faculty governance committees. BLS OES reports 122,380 employed under 25-1199; median annual wage $74,100. |
| What This Role Is NOT | NOT health specialties teachers (SOC 25-1071, 70.9 Green Transforming — clinical supervision protection). NOT teaching assistants, postsecondary (SOC 25-9044, 22.0 Red — grading-dominated, no research mandate). NOT K-12 teachers (state-licensed, child safeguarding, acute shortage). NOT cybersecurity professors (niche subject, growing demand). NOT education administrators (management role, no teaching). |
| Typical Experience | 5-15+ years. Ph.D. or terminal degree typically required for tenure-track at 4-year institutions. Master's sufficient for community colleges and continuing education. Active research/publication record expected at research universities. May hold tenure or be on tenure track at this level. |
Seniority note: Entry-level adjuncts and lecturers without tenure protection, research mandate, or governance responsibilities would score deeper Yellow or borderline Red — they lack the structural barriers and task diversity that protect mid-to-senior faculty. A department chair adds administrative leadership that would score similarly to Education Administrator, Postsecondary (47.0).
Protective Principles + AI Growth Correlation
| Principle | Score (0-3) | Rationale |
|---|---|---|
| Embodied Physicality | 1 | Campus and classroom presence expected — lectures, seminars, office hours, lab supervision. But the environment is structured and predictable. COVID demonstrated that much of the work can function remotely (though suboptimal). No clinical supervision, no unstructured physical environments. Far less physical protection than K-12 teachers or health specialties faculty. |
| Deep Interpersonal Connection | 2 | Mentoring graduate students through dissertations, advising on career paths, building trust with advisees over years, guiding students through intellectual development. The faculty-student relationship in advanced study is meaningful and trust-dependent. Less visceral than K-12 (adult students, not children) but significant at mid-to-senior level where mentoring intensifies. |
| Goal-Setting & Moral Judgment | 2 | Sets research direction, designs curricula for emerging/interdisciplinary fields, makes academic integrity decisions, evaluates student progression, participates in tenure and promotion decisions for peers, shapes programme direction. Regular judgment calls in ambiguous situations — but bears less institutional accountability than administrators or K-12 principals. |
| Protective Total | 5/9 | |
| AI Growth Correlation | 0 | Neutral. AI adoption does not create or destroy demand for these faculty. Demand is driven by student enrolment, institutional programme decisions, and faculty turnover. Some new AI-related interdisciplinary teaching emerges (AI ethics, responsible AI) but does not create net new positions at scale. |
Quick screen result: Protective 5/9 = Likely Yellow Zone. Proceed to quantify.
Task Decomposition (Agentic AI Scoring)
| Task | Time % | Score (1-5) | Weighted | Aug/Disp | Rationale |
|---|---|---|---|---|---|
| Classroom teaching & lecture delivery — lectures, seminars, workshops, discussions, interdisciplinary courses | 25% | 3 | 0.75 | AUGMENTATION | AI generates lecture outlines, slides, case studies, reading lists, and interactive exercises. Faculty delivers content, leads Socratic discussion, brings interdisciplinary expertise, adapts to student questions. For continuing education and professional development components, content is more standardised and AI handles more. Human-led but significantly AI-accelerated across the diverse subjects in this catch-all. |
| Student assessment & grading — exams, essays, research papers, presentations, oral defences | 15% | 3 | 0.45 | AUGMENTATION | Gradescope handles MCQs and structured assessments. AI provides first-pass feedback on written work. Mid-to-senior faculty delegate routine grading to TAs and AI tools, focusing on complex assessment — evaluating research quality, intellectual originality, and academic progression. The gatekeeping decisions (pass/fail, honours) require faculty judgment. |
| Research & scholarly activity — conducting research, writing papers, presenting at conferences, applying for grants, peer review | 20% | 2 | 0.40 | AUGMENTATION | AI accelerates literature review, data analysis, and draft generation. But original research questions, interdisciplinary synthesis, study design, ethical review (IRB), and peer review require human judgment. Mid-to-senior faculty drive research agendas and the intellectual contribution is irreducibly human. |
| Curriculum development & programme design — creating new courses, designing interdisciplinary programmes, aligning with accreditation standards | 10% | 3 | 0.30 | AUGMENTATION | AI drafts syllabi, generates learning outcomes, creates course materials, and suggests assessment strategies. Faculty make strategic decisions about what to teach, how to connect disciplines, and what emerging fields to incorporate. Accreditation alignment requires human expertise. |
| Student mentoring & advising — graduate supervision, career guidance, dissertation mentorship, academic counselling, recommendation letters | 10% | 1 | 0.10 | NOT INVOLVED | Personal mentoring through intellectual development — guiding a doctoral student's research, supporting career decisions, writing recommendation letters, navigating the academic job market. Human connection IS the value. |
| Committee work & academic governance — faculty senates, search committees, programme reviews, peer evaluation, tenure committees | 10% | 2 | 0.20 | AUGMENTATION | Faculty governance is political, relational, and judgment-intensive. Tenure decisions, faculty hiring, programme reviews, and institutional policy require human deliberation. AI helps with documentation and analysis but the decisions are committee-driven and inherently human. |
| Administrative tasks & professional development — scheduling, email management, grant administration, progress reports, conference logistics | 10% | 4 | 0.40 | DISPLACEMENT | Scheduling, email triage, grant reporting, travel coordination, attendance tracking, and progress documentation are increasingly handled by AI-powered administrative systems end-to-end. Faculty review and sign off but the manual work is largely displaced. |
| Total | 100% | 2.60 |
Task Resistance Score: 6.00 - 2.60 = 3.40/5.0
Displacement/Augmentation split: 10% displacement, 80% augmentation, 10% not involved.
Reinstatement check (Acemoglu): AI creates new tasks — integrating AI literacy into interdisciplinary curricula, teaching students to critically evaluate AI-generated content, developing assessment strategies that account for AI capabilities, conducting research on AI's impact within their field, validating AI-generated course materials for accuracy, and navigating institutional AI use policies. These oversight and integration tasks are growing but do not yet create net new positions.
Evidence Score
| Dimension | Score (-2 to 2) | Evidence |
|---|---|---|
| Job Posting Trends | +1 | BLS projects 7% growth for postsecondary teachers overall 2024-2034 (+96,700 jobs) — faster than average. The catch-all benefits from new interdisciplinary programmes and emerging fields. Not surging, but positive growth driven by replacement needs (retirements) and programme expansion. The enrolment cliff creates headwinds at some institutions but net growth remains positive. |
| Company Actions | 0 | No universities are cutting faculty positions citing AI. The adjunctification trend (more contingent, fewer tenure-track) continues but predates AI and is driven by cost pressure, not automation. Some programme expansions in interdisciplinary/emerging fields offset by small-college closures from demographics. No clear AI-driven changes to headcount. |
| Wage Trends | 0 | Median $74,100 for 25-1199 (below the $83,980 all-postsecondary median, reflecting the catch-all's inclusion of lower-paid continuing education and adjunct-heavy positions). Growing roughly with inflation. No significant premium signals specific to this catch-all. STEM-adjacent interdisciplinary faculty command higher salaries; humanities-oriented catch-all roles trail. |
| AI Tool Maturity | 0 | Production tools deployed: Gradescope (grading), MagicSchool.ai (lesson planning), Khanmigo (student tutoring), ChatGPT (content generation). All augmentative — none replaces the professor in the classroom, in research, or in mentoring. AI grading limited for nuanced written assessment. Tools in widespread early adoption but unclear impact on faculty headcount. |
| Expert Consensus | +1 | Brookings/McKinsey: education has among the lowest automation potential (<20% of tasks). WEF: 78% of education experts say AI augments not replaces. CDT/EdWeek (2025): 85% of teachers used AI during 2024-25, all for augmentation. EDUCAUSE (2026): AI reshaping work in higher ed — focused on augmentation. Consensus: faculty roles transform, not disappear. |
| Total | 2 |
Barrier Assessment
Reframed question: What prevents AI execution even when programmatically possible?
| Barrier | Score (0-2) | Rationale |
|---|---|---|
| Regulatory/Licensing | 1 | No state licence required (unlike K-12 teachers). However, regional accreditation bodies (HLC, SACSCOC, MSCHE) require qualified faculty — typically terminal degrees. Professional accreditors set faculty credential standards. EU AI Act classifies education as high-risk AI, mandating human oversight. FERPA governs student data. Substantial regulatory framework but not as hard a barrier as state licensing. |
| Physical Presence | 1 | Classroom presence expected for lectures, seminars, and office hours. But the environment is structured and predictable. COVID proved remote teaching workable (if suboptimal). Many programmes now hybrid or fully online. No clinical supervision of patients, no child safeguarding. Moderate barrier that erodes as online delivery expands. |
| Union/Collective Bargaining | 1 | AAUP, AFT, and NEA represent faculty at many public universities. Tenure system protects mid-to-senior faculty at research institutions — this is the strongest structural protection for this seniority level. But tenure is not universal (community colleges, private institutions), and the adjunctification trend bypasses it. |
| Liability/Accountability | 1 | Academic integrity decisions, grade appeals, research integrity (IRB compliance), and student progression carry professional consequences. But lower stakes than health professions — no patient safety liability, no criminal exposure for teaching outcomes. Moderate: faculty bear professional reputation risk but not personal legal liability for pedagogical decisions. |
| Cultural/Ethical | 1 | Society expects human professors, and academic tradition values human scholarship and teaching. Students prefer human instruction for complex and interdisciplinary topics. But the cultural attachment is less visceral than K-12 (adult students, not children) and less safety-critical than health education. Moderate cultural resistance rooted in tradition rather than safety anxiety. |
| Total | 5/10 |
AI Growth Correlation Check
Confirmed 0 (Neutral). AI adoption does not create or destroy demand for these faculty. Demand is driven by student enrolment, institutional programme decisions, and faculty turnover — all largely independent of AI deployment. Some new AI-adjacent interdisciplinary teaching (AI ethics, digital humanities, responsible AI) creates work within existing roles but does not generate net new faculty positions. The enrolment cliff is the dominant demand driver, and it operates independently of AI.
JobZone Composite Score (AIJRI)
| Input | Value |
|---|---|
| Task Resistance Score | 3.40/5.0 |
| Evidence Modifier | 1.0 + (2 × 0.04) = 1.08 |
| Barrier Modifier | 1.0 + (5 × 0.02) = 1.10 |
| Growth Modifier | 1.0 + (0 × 0.05) = 1.00 |
Raw: 3.40 × 1.08 × 1.10 × 1.00 = 4.0392
JobZone Score: (4.0392 - 0.54) / 7.93 × 100 = 44.1/100
Zone: YELLOW (Green ≥48, Yellow 25-47, Red <25)
Sub-Label Determination
| Metric | Value |
|---|---|
| % of task time scoring 3+ | 60% |
| AI Growth Correlation | 0 |
| Sub-label | Yellow (Urgent) — AIJRI 25-47 AND ≥40% of task time scores 3+ |
Assessor override: None — formula score accepted. The 44.1 sits 3.9 points below the Green threshold (48). The gap is honest: this catch-all lacks the clinical supervision that protects Health Specialties Teachers (70.9), the child safeguarding that protects K-12 teachers (68-75), and the acute shortage signals that boost evidence for both. The 26.8-point gap from Health Specialties Teacher reflects five real structural differences: no clinical patient supervision (30% of health specialties time at score 1), no professional licensure, no patient safety liability, weaker evidence (+2 vs +7), and weaker barriers (5 vs 8). The bimodal nature of this catch-all — tenured R1 professors vs. adjunct continuing education instructors — means the average is the correct assessment for the occupation, with variance addressed in Step 7.
Assessor Commentary
Score vs Reality Check
The 44.1 composite and Yellow (Urgent) label are 3.9 points from Green — a borderline score. This assessment is NOT barrier-dependent: stripping barriers entirely (modifier 1.00 instead of 1.10), the score would drop to ~40.1, still Yellow. The task decomposition is the primary driver. The catch-all nature of SOC 25-1199 creates genuine bimodality — tenured research professors at R1 universities are functionally Green (strong task protection through research + mentoring, tenure as structural barrier), while adjunct continuing education instructors are functionally deeper Yellow or Red-adjacent (standardised content delivery, no tenure, no research mandate, high displacement risk). The 44.1 average is the honest composite for the occupation.
What the Numbers Don't Capture
- The enrolment cliff is the real headcount threat, not AI. Declining 18-year-old population from the 2008 birth rate dip will reduce college enrolment starting 2025-2028, particularly at smaller, non-selective institutions where catch-all faculty concentrate. This demographic signal compounds AI transformation pressure.
- Adjunctification compresses the protected core. As universities replace tenure-track positions with contingent faculty, the structural protections (tenure, research mandate, governance participation) that distinguish mid-to-senior from entry-level erode. A faculty member hired as an adjunct in 2026 faces fundamentally different risk than one who earned tenure in 2016.
- The catch-all masks enormous discipline variation. A professor of digital humanities at a research university does different work than a continuing education instructor teaching professional development workshops. Same SOC code, different zones. The interdisciplinary faculty in emerging fields may actually be creating the most AI-resistant version of this role — because their fields are novel and require human synthesis.
- Function-spending vs people-spending. Universities are investing heavily in AI platforms (adaptive learning, automated grading, student analytics) that increase per-faculty productivity. This investment may sustain or even grow programme capacity while reducing headcount growth — the market for higher education grows but the number of human faculty needed per student may decline.
Who Should Worry (and Who Shouldn't)
Tenured or tenure-track professors at research universities who combine active research, graduate mentoring, interdisciplinary teaching, and faculty governance are the safest version of this role. Their work is intellectually original, relationship-heavy, and structurally protected by tenure. They're functionally Green regardless of the label. Adjunct and contingent faculty who primarily deliver standardised lectures, grade routine assignments, and have no research mandate or governance role should pay serious attention. Their tasks are the most AI-acceleratable, and the enrolment cliff may eliminate their positions before AI does. Continuing education and professional development instructors face the highest risk within this catch-all — their content is often standardised, their student relationships are transactional, and AI tutoring platforms (Khanmigo, ChatGPT Study Mode) directly compete with their delivery model. The single biggest separator: whether your role involves original intellectual contribution (research, interdisciplinary synthesis, mentoring) or routine content delivery (standardised lectures, template-based assessment). The more your work looks like what AI already does well — generating content, grading structured work, delivering established curricula — the more exposed you are.
What This Means
The role in 2028: Postsecondary faculty in this catch-all use AI to generate lecture materials, grade routine assignments, create adaptive learning modules, and handle administrative overhead. The time saved goes into what AI cannot do — original research, interdisciplinary programme design, graduate mentoring, and faculty governance. The faculty member who embraces AI tools teaches more effectively with less prep time. The one who resists them falls behind colleagues who produce more research, mentor more students, and contribute more to institutional governance.
Survival strategy:
- Build an active research programme — original scholarly contribution is the most AI-resistant task in academia. Faculty who publish, present, and secure grants demonstrate irreplaceable intellectual value that no AI replicates
- Deepen mentoring and advising relationships — graduate student supervision, career guidance, and intellectual mentorship are irreducibly human. Make yourself indispensable to students' professional development
- Adopt AI tools aggressively for teaching and grading — use Gradescope, MagicSchool.ai, and LLMs to eliminate the mechanical work that consumes 25-40% of faculty time, and reinvest in research, mentoring, and curriculum innovation
Where to look next. If you're considering a career shift, these Green Zone roles share transferable skills with postsecondary teaching:
- Education Administrator, K-12 (AIJRI 59.9) — Academic leadership, curriculum oversight, faculty management, and compliance expertise transfer directly. Requires state administrator certification but pedagogical foundation aligns.
- Elementary School Teacher (AIJRI 70.0) — Teaching, curriculum design, assessment, and student mentoring skills transfer directly. Requires state licensure but stronger structural protections (child safeguarding, acute shortage, union representation).
- Compliance Manager (AIJRI 48.2) — Research, documentation, regulatory knowledge, governance, and stakeholder communication transfer well. Especially relevant for faculty with heavy accreditation or programme review experience.
Browse all scored roles at jobzonerisk.com to find the right fit for your skills and interests.
Timeline: 3-5 years for the teaching and grading layers to transform substantially; 10+ years for the research and mentoring core to face meaningful pressure. Driven by the convergence of AI-powered educational tools, the enrolment cliff, and continued adjunctification — which together will consolidate routine teaching positions while preserving research-active, mentorship-heavy faculty roles.
