# JobZone — AI Job Replacement Index (Full Content)

> Generated: 2026-03-30 | 3649 roles assessed
> Source: https://jobzonerisk.com

## AIJRI Methodology Summary

The AI Job Resistance Index (AIJRI) scores every role 0-100 for AI displacement
risk using an 8-step framework:

1. **Role Selection** — identify the specific occupation and seniority level
2. **Task Decomposition** — break the role into 5-10 weighted constituent tasks
3. **Evidence Gathering** — collect labour market data, company actions, AI tool maturity, and academic research
4. **Task Resistance Scoring** — score each task 1-5 for agentic AI automation potential
5. **Composite Scoring** — multiply four dimensions: Task Resistance, Evidence modifier, Barrier modifier, Growth modifier
6. **Zone Classification** — map the normalised 0-100 score to RED, YELLOW, or GREEN
7. **Practical Recommendations** — generate actionable career guidance based on score and zone
8. **Quality Assurance** — cross-validate evidence, check for bias, apply TruthSeeker fact-checking

The composite formula is multiplicative (Raw = TRS x E_mod x B_mod x G_mod),
meaning weakness in any single dimension drags the overall score down — strength
elsewhere cannot compensate.

## Zone Definitions

- **GREEN (48-100):** Role is protected or growing. Safe for 5+ years.
  - Green Accelerated (80-100): AI actively increases demand
  - Green Stable (64-79): Fundamentally resistant to automation
  - Green Transforming (48-63): Safe but workflow is changing
- **YELLOW (25-47):** Role is transforming. 2-7 years to adapt.
  - Yellow Moderate (36-47): Significant changes coming
  - Yellow Urgent (25-35): Rapid transformation underway
- **RED (0-24):** Role is being actively displaced. Act now.
  - Red (10-24): Substantial automation pressure
  - Red Imminent (0-9): Near-complete displacement likely

## Frequently Asked Questions

### What is JobZone Risk?
JobZone Risk is a free tool that scores how resistant your job is to AI displacement. Every role gets a JobZone Score from 0 to 100 — higher means more resistant. Scores map to three zones: Green (resistant, 48–100), Yellow (transforming, 25–47), and Red (vulnerable, 0–24). The full scoring methodology is published openly.

### Will AI take my job?
It depends on the specific role and seniority level. Most jobs won’t vanish overnight — they’ll transform. The dominant near-term impact of AI is role transformation, not outright elimination. Yellow is consistently the largest zone in our assessments. That said, some entry-level roles with highly automatable tasks are already seeing displacement. Search for your role to see its specific score and what the evidence says.

### What do the Green, Yellow, and Red zones mean?
Green (48–100): The role is protected or growing. Safe for 5+ years based on current AI trajectories. Yellow (25–47): The role is transforming. You have 2–7 years to adapt your skills. The job won’t disappear, but it will change significantly. Red (0–24): The role is being actively displaced. Act now — upskill, pivot, or move into a more senior version of the role. Each zone has sub-labels (e.g., Green Accelerated, Yellow Urgent, Red Imminent) that give more precise guidance. See the zone classification system for the full breakdown.

### How do I find my job's score?
Go to the homepage and search by job title. You can also filter by zone (Green, Yellow, Red) or browse by professional domain. Each role page includes the full JobZone Score, task breakdown, evidence summary, and practical recommendations.

### Why does seniority matter so much?
Stanford research found that workers aged 22–25 in AI-exposed roles saw −13% employment since 2022, while older workers in the same occupations grew 6–9%. Junior roles tend to involve repetitive, well-defined tasks that AI handles well. Senior roles involve judgment, stakeholder management, strategic thinking, and accountability — tasks AI cannot yet perform autonomously. For example, a Junior Software Developer scores 9.3 (Red) while a Senior Software Engineer scores 55.4 (Green). Same field, different zones.

### What should I do if my job is in the Red zone?
Red doesn’t mean “fired tomorrow” — it means the displacement pressure is real and accelerating. Three practical moves: Move up: Senior versions of the same role often score much higher. Invest in experience and certifications. Move sideways: Use the Compare Roles tool to find adjacent roles in a safer zone. Become the operator: Learn to work with AI tools in your field. The people who deploy and manage AI systems in each domain will be the last to be displaced.

### Are these scores perfect? Should I make career decisions based on them?
No — and we want to be upfront about that. JobZone Scores are not perfect. They are structured analytical assessments, not empirical predictions. The scoring involves expert judgment, and there can be errors, outdated evidence, or gaps in the data. Two reasonable assessors could produce different scores for the same role. You should not make major career decisions based solely on a JobZone Score. Use it as one input alongside your own research, industry knowledge, conversations with people in the field, and professional career advice. A score can highlight risks you hadn’t considered or confirm what you already suspected — but it’s a starting point for investigation, not a final verdict. We publish our full methodology and 15 known limitations precisely so you can judge the strengths and weaknesses for yourself.

### How often are scores updated?
We target a 6-month refresh cycle for high-volatility roles (Red, Yellow Urgent) and 12 months for stable roles (Green). AI capability changes quarter by quarter, so published scores may become less accurate between refresh cycles. Each assessment shows its date of last review.

### How is the JobZone Score calculated?
The score uses a multiplicative composite formula: Raw = TRS × Emod × Bmod × Gmod Four dimensions multiply together: Task Resistance Score (how hard tasks are to automate), Evidence modifier (what the labour market shows), Barrier modifier (regulatory, physical, and cultural protections), and Growth modifier (whether demand rises or falls with AI). The raw result is normalised to 0–100. The full formula and worked examples are in the Composite Scoring Model section.

### Why is it multiplicative, not additive?
Because weakness in any dimension should drag the score down proportionally — not be hidden by strength elsewhere. A role with highly resistant tasks but collapsing market evidence should NOT score Green. The market has spoken. This non-compensatory property is borrowed from CVSS (vulnerability scoring) and the UN Human Development Index’s geometric mean approach, where poor health can’t be offset by high income.

### What data sources do you use?
Every assessment draws from multiple tiers: labour market data (Indeed, LinkedIn, Glassdoor, Google Jobs, USAJobs, Reed), company actions from 79 curated RSS feeds and earnings calls, AI tool maturity reviews, academic research via Semantic Scholar (220M+ papers), and regulatory/licensing databases. Evidence is cross-validated across independent search engines — when two engines return the same article, that counts as one source, not two. See the Data Sources section for the full breakdown.

### How are individual tasks scored?
Each role is decomposed into 5–10 constituent tasks, weighted by percentage of total role time. Each task is scored 1–5 for agentic AI automation potential: 1 — Irreducible Human: Protected by legal accountability, ethical judgment, trust 2 — Barrier-Protected: Requires licensed professional judgment 3 — Human-Led, AI-Accelerated: AI handles sub-workflows, human leads 4 — Agent-Executable: AI agent can execute end-to-end 5 — Fully Automatable: Deterministic, AI already performs at scale The question isn’t “can AI assist?” but “can an AI agent execute this entire workflow without a human?”

### What is the TruthSeeker protocol?
Every factual claim in an assessment passes through a 12-phase fact-checking protocol adapted from professional journalism and intelligence analysis. It applies methods from the IFCN (International Fact-Checking Network), the SIFT method by Mike Caulfield, and Analysis of Competing Hypotheses from intelligence tradecraft. Claims receive a confidence score (0–100) and a structured verdict. Claims that can’t be verified to a high threshold are excluded or explicitly flagged. See Section 3.4 for the full protocol.

### Can I trust these scores?
We designed the scoring to be maximally transparent precisely so you can judge for yourself. Every rubric, coefficient, and formula is published. Every assessment shows its task decomposition, evidence sources, and modifier calculations. We list 15 known limitations openly. That said, the task resistance score at the heart of each assessment is a structured expert judgment, not an empirical measurement. Two reasonable assessors could disagree by enough to shift a zone boundary. We describe the modifiers as “evidence-informed” rather than “evidence-based” because the underlying task scoring remains a judgment call.

### What assumptions does the scoring make?
Every scoring framework rests on assumptions. We want to be explicit about ours: Sub-AGI AI: The methodology assumes increasingly capable, agentic AI — not artificial general intelligence (AGI). If AGI arrives, the question shifts from “what can AI do?” to “what should AI be allowed to do?” and all scores would need rethinking. 3–5 year horizon: Scores reflect near-to-medium term displacement risk based on current AI trajectories, not long-term predictions about 2035 or beyond. Roles, not individuals: We assess occupations as categories. A uniquely skilled individual in a Red-zone role may have personal expertise that the aggregate score doesn’t capture. Your mileage may vary. Western labour markets: Evidence sources are predominantly US/UK-centric (BLS, O*NET, Indeed, LinkedIn). Scores may not transfer to markets with different regulatory frameworks, union structures, or technology adoption rates. Current regulations hold: We model existing barriers (licensing, regulation, liability) but don’t predict future AI legislation. Major new regulation (like the EU AI Act or potential US laws) could materially shift scores. No robotics breakthrough: Physical trades score highly partly because humanoid robotics hasn’t achieved dexterity in unstructured environments. If that changes, trades scores would need revision. The worker adapts (or doesn’t): Many Yellow-zone assessments carry an implicit assumption that the practitioner will adopt AI tools. If you refuse to adapt, a Yellow score may understate your risk. If you’re already ahead of the curve, it may overstate it. Task decomposition is representative: Each role is broken into 5–10 weighted tasks. Different employers may structure the same role differently, shifting which tasks dominate. These assumptions are stated formally in Section 1.1 of the methodology and revisited in the Limitations section. If any of them don’t hold for your situation, adjust your interpretation accordingly.

### How many jobs have you assessed?
The corpus covers occupations across 25 domains and over 150 specialisms, assessed on a rolling basis targeting 90% US workforce coverage by employment volume. Browse the full corpus to see all assessed roles.

### Is this just for US workers?
The primary evidence sources are US/UK-centric (BLS, O*NET, Indeed, LinkedIn). Scores may not fully transfer to labour markets with different regulatory frameworks, union structures, or technology adoption rates. That said, the core AI capability assessment (can AI do these tasks?) is largely geography-independent. The modifiers — especially barriers and evidence — reflect Western labour market conditions. We acknowledge this as a known limitation.

### Who created this?
JobZone Risk was developed by Nathan House and HAL (an AI research system) at StationX Research. Nathan has 30 years of cybersecurity experience and has trained over 500,000 students globally. The methodology is published openly for peer review and independent replication. Learn more.

### Is the methodology open for peer review?
Yes. The complete methodology, all scoring rubrics, coefficients, normalisation constants, and worked examples are published at /methodology. We actively invite scrutiny. The interactive calculator lets you test how different inputs produce different outputs. If our scores are wrong, tell us where and we will correct them.

## Example Roles: Safest from AI (Top 10)

### Electrical Power-Line Installer and Repairer (Mid-Level)
- **AIJRI Score:** 91.6 | **Zone:** GREEN (Stable)
- Among the most AI-resistant roles in the entire economy. Physical work at extreme heights with high-voltage lines in unstructured, unpredictable environments makes this role virtually untouchable by AI or robotics for decades. Safe for 15-25+ years.

### Signalling Tester In Charge / STIC (Mid-Level)
- **AIJRI Score:** 87.7 | **Zone:** GREEN (Stable)
- Safety-critical physical testing in unstructured trackside environments, IRSE licensing, and personal go/no-go certification authority make this one of the most AI-resistant roles in rail engineering. Acute skills shortage and ETCS rollout sustain structural demand for decades. Safe for 15+ years.

### Model Alignment Researcher (Mid-Level)
- **AIJRI Score:** 86.1 | **Zone:** GREEN (Accelerated)
- Alignment research is irreducibly human intellectual work that grows in demand with every advance in AI capability. More powerful models require more sophisticated alignment techniques — a recursive dependency that makes this one of the most protected roles in the economy. Safe for 10+ years.

### AI Safety Researcher (Mid-Senior)
- **AIJRI Score:** 85.2 | **Zone:** GREEN (Accelerated)
- This role strengthens with every advance in AI capability. More powerful AI systems demand more safety research — a recursive dependency that makes this one of the most AI-resistant positions in the economy. Safe for 10+ years.

### Foster Carer (Mid-Level)
- **AIJRI Score:** 84.5 | **Zone:** GREEN (Stable)
- Foster care is among the most AI-resistant work in the economy — 24/7 physical parenting of traumatised children in an unstructured home, with deep emotional bonding, real-time judgment, and heavy regulation making displacement inconceivable. Safe for 5+ years.

### Leadworker (Mid-Level)
- **AIJRI Score:** 83.7 | **Zone:** GREEN (Stable)
- Lead sheet work on heritage buildings is among the most AI-resistant trades in existence -- a dying art requiring years of hand-skill mastery in extreme physical environments that no robot can navigate. Safe for 5+ years with an acute and worsening workforce shortage.

### Heat Pump Installer (Mid-Level)
- **AIJRI Score:** 83.5 | **Zone:** GREEN (Transforming)
- Near-maximum Green — UK government targets, record installations, severe MCS-certified installer shortage, and irreducible physical work converge. Every installation involves drilling through walls, running pipework, handling refrigerants, and commissioning in unpredictable residential environments. AI assists with heat loss calculations and admin, but cannot install a heat pump. The gas boiler phase-out creates a decade of guaranteed demand growth with no AI displacement pathway.

### Trauma Surgeon (Mid-to-Senior)
- **AIJRI Score:** 83.2 | **Zone:** GREEN (Stable)
- One of the most AI-resistant roles in medicine. Unstructured emergency surgery in hemorrhaging patients is decades beyond any robotic or AI capability. Safe for 15+ years.

### CCS Engineer (Control Command & Signalling) (Mid-Level)
- **AIJRI Score:** 83.2 | **Zone:** GREEN (Stable)
- Hands-on trackside installation and commissioning of safety-critical signalling systems in unstructured rail environments, combined with IRSE licensing, personal safety accountability, and acute skills shortage, makes this one of the most AI-resistant engineering roles. Safe for 15+ years.

### Chief Information Security Officer (CISO) (Senior/Executive)
- **AIJRI Score:** 83 | **Zone:** GREEN (Accelerated)
- The CISO role is deeply protected by irreducible accountability, board-level trust, and strategic judgment that AI cannot replicate or be permitted to assume. Demand is growing, compensation rising 6.7% YoY, and AI adoption expands the CISO's mandate rather than shrinking it. 10+ year horizon, likely indefinite.

## Example Roles: Most At Risk (Top 10)

### File Clerks (Mid-Level)
- **AIJRI Score:** 1.5 | **Zone:** RED (Imminent)
- Filing, sorting, retrieving, and storing records — physical or digital — is exactly the work that document management systems, OCR, and AI-powered classification were built to eliminate. BLS projects steep decline for 43-4071; production tools have automated 95% of core tasks across every industry. Displacement is not a forecast — it is the present reality.

### Micro-Task Worker (Online) (Mid-Level)
- **AIJRI Score:** 1.7 | **Zone:** RED (Imminent)
- AI is already performing the core tasks — data labelling, image tagging, transcription, and content classification — at scale, faster, and cheaper than human micro-task workers. Displacement is underway now with 12-24 months to near-complete automation of basic platform tasks.

### Data Entry Keyer (Mid-Level)
- **AIJRI Score:** 2.3 | **Zone:** RED (Imminent)
- Data entry — keying information from source documents into computers — is the task OCR, IDP, and RPA were literally built to replace. Production tools already perform 95%+ of this role's core tasks autonomously at higher speed and accuracy. BLS projects -25.9% decline, one of the steepest in all occupations. Displacement is not approaching — it has arrived.

### Word Processor and Typist (Mid-Level)
- **AIJRI Score:** 2.6 | **Zone:** RED (Imminent)
- AI text generation, speech-to-text, OCR, and document automation have already displaced the core typing and transcription functions. BLS projects employment decline of 38% by 2033, one of the steepest declines in any occupation. This role is being eliminated within 12-36 months at organisations that adopt modern document tools.

### Vulnerability Tester / Scanner Operator (Entry-Level)
- **AIJRI Score:** 2.7 | **Zone:** RED (Imminent)
- This role is the most directly automated function in cybersecurity — AI platforms perform the complete scan-triage-prioritize-report workflow end-to-end. The dedicated role is ceasing to exist. Act now.

### Telephone Operator (Mid-Level)
- **AIJRI Score:** 3 | **Zone:** RED (Imminent)
- AI voice agents, IVR with natural language processing, and automated directory assistance have eliminated the vast majority of telephone operator positions. Employment has fallen to 4,000 nationally with only 300 projected openings over the next decade. Displacement is not approaching — it is nearly complete.

### Virtual Assistant (Entry-to-Mid Level)
- **AIJRI Score:** 3.2 | **Zone:** RED (Imminent)
- Every core task -- email triage, scheduling, data entry, travel booking, social media posting -- has production AI tools performing the work end-to-end. Zero structural barriers. The gig economy model that defines this role accelerates displacement because clients can switch to AI platforms overnight. Act now.

### Live Chat Support Agent (Entry-to-Mid Level)
- **AIJRI Score:** 3.4 | **Zone:** RED (Imminent)
- AI chatbots are production-deployed across every major support platform, autonomously resolving 60-80% of live chat volume end-to-end. Text-based, structured, easily parsed by LLMs — live chat is the single most automatable customer service channel. Displacement is not coming; it has arrived.

### Telemarketer (Mid-Level)
- **AIJRI Score:** 3.4 | **Zone:** RED (Imminent)
- AI voice agents already make thousands of outbound calls per day at a fraction of the cost of a human caller. BLS projects -22.1% decline by 2034. With zero structural barriers and universal expert consensus on displacement, this is one of the most exposed roles in the economy. Act immediately.

### Medical Transcriptionist (Mid-Level)
- **AIJRI Score:** 3.6 | **Zone:** RED (Imminent)
- AI speech recognition has already displaced the core transcription function. Employment in active decline with BLS projecting further contraction. The standalone medical transcriptionist role is being eliminated within 12-36 months at most organisations.

## Domain Overview

### AI
- **Roles:** 39 | **Avg Score:** 56
- **Specialisms:**
  - AI/ML Engineering
  - Generative & Language AI
  - AI Research & Governance

### Agriculture
- **Roles:** 54 | **Avg Score:** 48
- **Specialisms:**
  - Farming & Livestock
  - Field Sports & Wildlife
  - Forestry & Timber
  - Landscaping & Grounds

### Business & Operations
- **Roles:** 324 | **Avg Score:** 30
- **Specialisms:**
  - Executive Leadership
  - Project & Product Management
  - Operations Management
  - Sales
  - Finance & Accounting
  - Admin & Office
  - HR & People
  - Marketing
  - Procurement
  - Insurance
  - Banking & Lending
  - Investment & Securities
  - Consulting

### Cloud & Infrastructure
- **Roles:** 79 | **Avg Score:** 35
- **Specialisms:**
  - Cloud Architecture
  - DevOps & Platform
  - Networking
  - Systems Administration
  - IT Support
  - IT Administration
  - Database Administration
  - Site Reliability
  - IT Leadership

### Creative & Media
- **Roles:** 297 | **Avg Score:** 37
- **Specialisms:**
  - Design
  - Writing & Content
  - Performing Arts
  - Film & Video Production
  - Photography
  - Journalism & Publishing
  - Audio & Broadcasting
  - Interior Design
  - Fashion Design

### Cybersecurity
- **Roles:** 91 | **Avg Score:** 49
- **Specialisms:**
  - Application Security
  - Security Architecture
  - Security Audit
  - Cloud Security
  - Security Compliance
  - Security Education
  - Security Engineering
  - Cybersecurity Generalist
  - Security Governance
  - AI Security
  - Threat Intelligence
  - Cybersecurity Sales
  - Privacy
  - Security Operations
  - Offensive Security
  - Network Security
  - Digital Forensics & Investigation

### Data
- **Roles:** 40 | **Avg Score:** 29
- **Specialisms:**
  - Data Science & Analytics
  - Data Engineering

### Development
- **Roles:** 99 | **Avg Score:** 36
- **Specialisms:**
  - Software Development
  - Web Development
  - Mobile Development
  - QA & Testing
  - Game Development
  - Embedded & Firmware
  - Safety-Critical Software
  - Enterprise Platforms
  - Developer Tooling
  - Scientific & Financial Computing

### Education
- **Roles:** 146 | **Avg Score:** 49
- **Specialisms:**
  - Primary Teaching
  - Secondary Teaching
  - STEM & Health Academic
  - Humanities Academic
  - Social Sciences Academic
  - Senior Academic & Research
  - Special Education
  - Teaching Support
  - Education Administration
  - Early Childhood
  - Training & Development

### Engineering
- **Roles:** 194 | **Avg Score:** 46
- **Specialisms:**
  - Civil Engineering
  - Industrial Engineering
  - Mechanical Engineering
  - Electrical & Electronics Engineering
  - Chemical Engineering
  - Aerospace Engineering
  - Biomedical Engineering
  - Environmental Engineering
  - Architecture
  - Engineering Management
  - Engineering Technicians

### Government & Public Admin
- **Roles:** 97 | **Avg Score:** 42
- **Specialisms:**
  - Government Regulation & Enforcement
  - Government Administration
  - Judicial Services
  - Legislative & Policy
  - Postal Services

### Healthcare
- **Roles:** 379 | **Avg Score:** 58
- **Specialisms:**
  - Medicine
  - Surgery
  - Clinical Support
  - Caregiving
  - Pharmacy
  - Laboratory
  - Nursing
  - Health Administration
  - Physiotherapy
  - Occupational Therapy
  - Dental
  - Emergency Medicine
  - Diagnostic Imaging
  - Respiratory Sciences
  - Speech & Language Therapy
  - Dietetics & Nutrition
  - Mental Health

### Legal & Compliance
- **Roles:** 70 | **Avg Score:** 40
- **Specialisms:**
  - Advocacy & Prosecution
  - General Legal Practice
  - Corporate & Specialist Law
  - Judiciary
  - Legal Support

### Library, Museum & Archives
- **Roles:** 39 | **Avg Score:** 39
- **Specialisms:**
  - Library Services
  - Archival & Curation

### Manufacturing
- **Roles:** 239 | **Avg Score:** 31
- **Specialisms:**
  - Production Operations
  - Quality & Inspection
  - Warehousing
  - Metal & Plastics Processing
  - Textile & Garment
  - Chemical & Process Operation
  - Cutting & Forming
  - Assembly & Fabrication
  - Food Processing
  - Printing & Packaging

### Military
- **Roles:** 52 | **Avg Score:** 58
- **Specialisms:**
  - Ground Combat
  - Air Operations
  - Special Operations
  - Military Leadership
  - Military Intelligence
  - Military Support

### Public Safety
- **Roles:** 112 | **Avg Score:** 53
- **Specialisms:**
  - Law Enforcement
  - Corrections
  - Emergency Response
  - Dispatch & Communications
  - Protective Services
  - Private Investigation

### Real Estate & Property
- **Roles:** 42 | **Avg Score:** 35
- **Specialisms:**
  - Real Estate Sales
  - Property Management
  - Appraisal

### Religious & Community
- **Roles:** 30 | **Avg Score:** 54
- **Specialisms:**
  - Clergy & Ministry
  - Religious Education

### Retail & Service
- **Roles:** 249 | **Avg Score:** 41
- **Specialisms:**
  - Retail
  - Food Service
  - Customer Service
  - Hospitality
  - Personal Care

### Science & Research
- **Roles:** 118 | **Avg Score:** 41
- **Specialisms:**
  - Life Sciences
  - Physical Sciences
  - Environmental Science
  - Social Science
  - Mathematics & Statistics

### Social Services
- **Roles:** 67 | **Avg Score:** 56
- **Specialisms:**
  - Social Work
  - Counselling
  - Childcare

### Sports & Recreation
- **Roles:** 31 | **Avg Score:** 56
- **Specialisms:**
  - Sports Coaching
  - Fitness & Exercise
  - Leisure Management

### Trades & Physical
- **Roles:** 369 | **Avg Score:** 60
- **Specialisms:**
  - Electrical & Mechanical
  - Structural Trades
  - Finishing Trades
  - Heavy Equipment
  - Construction Support
  - Automotive
  - Welding
  - Plumbing & Pipefitting
  - HVAC
  - Painting & Finishing
  - Roofing
  - Masonry
  - Machining & CNC
  - Equipment & Vehicle Repair
  - Specialist Repair & Restoration
  - Facility Services

### Transportation
- **Roles:** 168 | **Avg Score:** 46
- **Specialisms:**
  - Transport & Logistics
  - Trucking
  - Public Transit
  - Aviation
  - Rail
  - Delivery & Courier
  - Logistics & Supply Chain
  - Maritime

### Utilities & Energy
- **Roles:** 110 | **Avg Score:** 51
- **Specialisms:**
  - Power Generation
  - Water & Wastewater
  - Drilling & Extraction
  - Refining & Gas Processing
  - Telecommunications
  - Mining Operations

### Veterinary & Animal Care
- **Roles:** 57 | **Avg Score:** 60
- **Specialisms:**
  - Veterinary Practice
  - Veterinary Support
  - Animal Care

## Comparison Tool

Compare any two roles side-by-side at [https://jobzonerisk.com/compare](https://jobzonerisk.com/compare).
See score deltas, task-level breakdowns, and transition paths between roles.
You can also compare entire domains or specialisms to identify the safest sectors.

## Stats & Research Articles

- [AI Labor Market Statistics [Mar 2026]](https://jobzonerisk.com/stats/ai-labor-market-statistics)
- [Most In-Demand Jobs Right Now [Mar 2026]](https://jobzonerisk.com/stats/most-in-demand-jobs)
- [AI and Job Loss Statistics [Mar 2026 Data]](https://jobzonerisk.com/stats/ai-and-job-loss)
- [AI Layoffs Statistics & Tracker [Mar 2026]](https://jobzonerisk.com/stats/ai-layoffs)
- [What Jobs Are Safe From AI? [Mar 2026]](https://jobzonerisk.com/stats/what-jobs-are-safe-from-ai)
- [Jobs That AI Cannot Replace [Mar 2026]](https://jobzonerisk.com/stats/jobs-that-ai-cannot-replace)
- [AI Statistics [Mar 2026 Data + Trends]](https://jobzonerisk.com/stats/ai-statistics)
- [AI Hype vs Reality (2026): We Scored 3,035+ Jobs](https://jobzonerisk.com/stats/ai-hype-vs-reality)
- [Fastest Growing Jobs [Mar 2026]](https://jobzonerisk.com/stats/fastest-growing-jobs)
- [What Jobs Will AI Replace by 2030? [Mar 2026]](https://jobzonerisk.com/stats/what-jobs-will-ai-replace-by-2030)
- [AI and Unemployment [Mar 2026]](https://jobzonerisk.com/stats/ai-and-unemployment)
- [Will AI Replace Humans? [Mar 2026 Analysis]](https://jobzonerisk.com/stats/ai-will-replace-humans)
- [AI and the Future of Work [Mar 2026]](https://jobzonerisk.com/stats/ai-and-the-future-of-work)
- [How Many Jobs Will AI Replace by 2050? [Mar 2026]](https://jobzonerisk.com/stats/how-many-jobs-will-ai-replace-by-2050)
- [Jobs Most at Risk From AI [Mar 2026]](https://jobzonerisk.com/stats/jobs-most-at-risk-from-ai)
- [Jobs Becoming Obsolete [Mar 2026]](https://jobzonerisk.com/stats/jobs-becoming-obsolete)
- [Most AI-Proof Jobs [Mar 2026]](https://jobzonerisk.com/stats/most-ai-proof-jobs)
- [Jobs AI Will Create [Mar 2026]](https://jobzonerisk.com/stats/jobs-ai-will-create)
- [Impact of AI on Employment [Mar 2026]](https://jobzonerisk.com/stats/impact-of-ai-on-employment)
- [High Paying AI-Proof Jobs [Mar 2026]](https://jobzonerisk.com/stats/high-paying-ai-proof-jobs)
- [AI and White-Collar Jobs [Mar 2026]](https://jobzonerisk.com/stats/ai-and-white-collar-jobs)
- [AI Job Loss Predictions [Mar 2026]](https://jobzonerisk.com/stats/ai-job-loss-predictions)
- [Engineering Jobs AI Can't Replace [Mar 2026]](https://jobzonerisk.com/stats/engineering-jobs-that-ai-cant-replace)
- [What Jobs Will AI Replace First? [Mar 2026]](https://jobzonerisk.com/stats/what-jobs-will-ai-replace-first)
- [Tech Jobs Safe From AI [Mar 2026]](https://jobzonerisk.com/stats/what-tech-jobs-are-safe-from-ai)
- [AI-Proof Jobs of the Future [Mar 2026]](https://jobzonerisk.com/stats/ai-proof-jobs-of-the-future)
- [AI Replacing Entry Level Jobs? [Mar 2026]](https://jobzonerisk.com/stats/ai-replacing-entry-level-jobs)
- [Cybersecurity Jobs Safe From AI [Mar 2026]](https://jobzonerisk.com/stats/are-cybersecurity-jobs-safe-from-ai)
- [Healthcare Jobs Safe From AI [Mar 2026]](https://jobzonerisk.com/stats/healthcare-jobs-safe-from-ai)
- [Finance Jobs Safe From AI [Mar 2026]](https://jobzonerisk.com/stats/finance-and-accounting-jobs-safe-from-ai)
- [Sales Jobs Safe From AI [Mar 2026]](https://jobzonerisk.com/stats/sales-jobs-safe-from-ai)
- [Trade Jobs Safe From AI [Mar 2026]](https://jobzonerisk.com/stats/trade-jobs-safe-from-ai)
- [AI & Graphic Design Jobs [Mar 2026]](https://jobzonerisk.com/stats/graphic-design-jobs-ai)
- [Blue Collar Jobs Safe From AI [Mar 2026]](https://jobzonerisk.com/stats/blue-collar-jobs-safe-from-ai)
- [Job Satisfaction Statistics by Profession [2026]](https://jobzonerisk.com/stats/job-satisfaction-statistics)
- [Blue vs White Collar AI Safety [Mar 2026]](https://jobzonerisk.com/stats/blue-collar-vs-white-collar-ai)

## REST API (Authenticated)

Full programmatic access via Bearer token authentication. [Documentation](https://jobzonerisk.com/api).

### Endpoints
- **GET /api/v1/roles** — Search and browse roles. Params: q (search), zone (GREEN/YELLOW/RED), domain, specialism, sort (select/score_asc/score_desc/alpha/alpha_desc/newest/oldest), page, per_page (max 100)
- **GET /api/v1/roles/:slug** — Full role details: AIJRI score, resistance/evidence/barrier scores, protective principles, AI growth correlation, specialisms, BLS employment, assessed date
- **GET /api/v1/stats/summary** — Total roles, average AIJRI score, zone distribution, workforce coverage
- **GET /api/v1/stats/zones** — Zone counts and BLS employment figures per zone
- **GET /api/v1/stats/domains** — Domain role counts, average scores, zone distribution
- **GET /api/v1/rankings/top?n=10** — Top N safest roles (default 10, max 100)
- **GET /api/v1/rankings/bottom?n=10** — Top N most at-risk roles
- **GET /api/v1/rankings/domain/:domain/top** — Safest roles within a domain
- **GET /api/v1/rankings/domain/:domain/bottom** — Most at-risk roles within a domain

### Authentication
All requests require: Authorization: Bearer jzr_your_key_here
Rate limit: 100 req/min per key (custom limits available). Headers: X-RateLimit-Limit, X-RateLimit-Remaining, X-RateLimit-Reset.
Errors use RFC 7807 Problem Details (application/problem+json).

## Widget API (Public, No Auth)

- **Search roles:** GET https://jobzonerisk.com/api/widget/search?q=term — returns matching roles as JSON
- **Role detail:** GET https://jobzonerisk.com/api/widget/job/:slug — returns full role data as JSON
- **Top/bottom lists:** GET https://jobzonerisk.com/api/widget/top?list=safest|at-risk&limit=N — returns ranked roles as JSON