Analyze / Jobs / Rankings / Special Education Teachers, Preschool Benchmark Job
Special Education Teachers, Preschool Special Education Teachers, Preschool is currently AI-resistant due to physical, trust-based, or high-judgment responsibilities.
Teach academic, social, and life skills to preschool-aged students with learning, emotional, or physical disabilities. Includes teachers who specialize and work with students who are blind or have visual impairments; students who are deaf or have hearing impairments; and students with intellectual disabilities.
21% exposure • High confidenceToday
Category: Educational Instruction and Library • Industry: Parole Offices and Probation Offices (92)
Top 3 drivers Routine process execution : 32% task weight, 35% automation potential.Documentation and reporting : 28% task weight, 25% automation potential.Stakeholder communication : 22% task weight, 11% automation potential.Top 2 blockers Exception handling : Edge cases and accountability ownership.Stakeholder communication : Empathy, negotiation, and situational nuance.Confidence reasons 1,016 benchmark role descriptions are mapped across O*NET + NAICS sources. Coverage spans 23 categories and 1,012 industries. Adjacent role consistency band is ±1 points for this benchmark family.
Task Mix ⓘ Routine process execution (32% weight • 11 contribution) 35%
High judgment, trust, or contextual complexity keeps this human-led.
Documentation and reporting (28% weight • 7 contribution) 25%
High judgment, trust, or contextual complexity keeps this human-led.
Stakeholder communication (22% weight • 2 contribution) 11%
High judgment, trust, or contextual complexity keeps this human-led.
Exception handling (18% weight • 0 contribution) 1%
High judgment, trust, or contextual complexity keeps this human-led.
Recommended Stack Click a stack item to open setup difficulty, time-to-value, and workflow details.
Learning content AI Planning automation Assessment assistant Replaceable tasks vs human tasks AI-suitable tasks ✓ Routine process execution 35% automation potential • Workflow automation + RPA ✓ Documentation and reporting 25% automation potential • Document AI + reporting automation ✓ Stakeholder communication 11% automation potential • Template assistant + CRM automation Human-needed tasks • Exception handling AI struggles because edge cases and accountability ownership. • Stakeholder communication AI struggles because empathy, negotiation, and situational nuance. • Documentation and reporting AI struggles because liability and audit-quality requirements. Tools coverage meter This stack covers 21% of automatable tasks.
Remaining gaps: exceptions, communication, edge cases.
Automation timeline Today tools now 12 months next wave 36 months agentic workflows
Current mode: Today • Exposure estimate: 21% • tools now
Safer adjacent roles Higher-paying adjacent roles Mathematicians Exposure: 27% • Salary: $160,000 • +$62,500 • Exposure tradeoff: +10 pts Arbitrators, Mediators, and Conciliators Exposure: 13% • Salary: $157,000 • +$59,500 • Exposure tradeoff: -4 pts Judicial Law Clerks Exposure: 18% • Salary: $156,000 • +$58,500 • Exposure tradeoff: +1 pts Administrative Law Judges, Adjudicators, and Hearing Officers Exposure: 21% • Salary: $155,500 • +$58,000 • Exposure tradeoff: +4 pts Lawyers Exposure: 19% • Salary: $149,000 • +$51,500 • Exposure tradeoff: +2 pts Physicists Exposure: 24% • Salary: $119,500 • +$22,000 • Exposure tradeoff: +7 pts Related roles Examples of automations Scheduling automation examples Capture requests from form/email into one queue Auto-propose slots using Scheduling workflow Send reminders and update status automatically Escalate conflicts to a supervisor with context Reporting automation examples Aggregate daily operations into one reporting table Generate dashboards with Reporting automation Create weekly summary narratives with risk flags Distribute summaries by role with required actions Communication templating examples Classify inbound messages by intent and urgency Draft replies with Communication copilot Insert policy-approved language and context snippets Queue sensitive drafts for manager approval Escalation handling examples Detect exception triggers from job events Route to specialist based on severity policy Attach timeline, customer context, and prior actions Track closure and feed outcomes into playbooks Benchmark data source Last updated: March 4, 2026
Benchmarked descriptions used: 1,016 role descriptions mapped across 1,012 industries.
Data references for this role Role profile and task mix
Job title, SOC 25-2051.00, role description, task statements, and job-zone context.
Source: O*NET Database 29.0 (Occupation Data + Job Zones) • O*NET Resource Center / U.S. Department of Labor
Industry and sector mapping
Industry code 922150, sector 92, and category mapping shown on this role.
Source: NAICS 2022 6-Digit Codes • U.S. Census Bureau
Exposure score, confidence, and timeline views
Deterministic benchmark scoring, confidence tiers, stack coverage, and timeline projections derived from role/task inputs.
Source: replaced.fyi methodology • replaced.fyi
Related roles and pivot recommendations
Adjacent-role comparisons and safer/higher-pay pivot suggestions computed from the same benchmark catalog.
Source: replaced.fyi rankings dataset • replaced.fyi
Primary source list Confidence definition: High confidence means broad role coverage, benchmark consistency across adjacent roles, and stable task-level scoring signals.
Methodology • Rankings