High Exposure, Lower Replacement Pressure
Substantial cognitive and documentation tasks overlap with AI, but statutory accountability, physical constraints, or institutional regulation buffer structural reduction.
Compare occupations by AI Exposure and Replacement Risk. See which jobs are highly exposed to AI, which face greater replacement pressure, and which remain more resilient because of human, physical, or structural factors.
This explorer maps occupations using two JobsVsAI measures. AI Exposure shows how much of the occupation’s task bundle overlaps with current AI capability. Replacement Risk shows how much of that exposure translates into structural pressure on the human role after physical constraints, accountability, and adoption realities are applied.
Jobs in this zone are both highly exposed to AI tasks and under elevated structural replacement pressure.
Occupations below the parity line show lower replacement pressure due to physical, accountability, and regulatory friction.
Occupations anchored in tactile trades and physical reality have lower exposure and lower replacement risk.
Search any occupation or filter by career field to inspect full task breakdowns and verified scores.
Plotting 507 verified occupations across capability exposure and structural risk.
AI can assist with substantial analysis or drafting, but human dependency, physical requirements, accountability, regulation, adoption, or labour-market friction buffer structural displacement.
e.g. Software Engineers, Nurse Practitioners, Financial AdvisorsHigh task overlap with algorithmic models, paired with standardized digital workflows and lower physical or regulatory barriers to commercial automation.
e.g. Telemarketers, Data Entry Keyers, Title ExaminersOccupations centered around unpredictable physical environments, fine manual manipulation, emergency intervention, or specialized tactile tradecraft.
e.g. Electricians, Commercial Divers, FirefightersLower overall AI capability overlap, but specialized structural or commercial vulnerability in specific routine or consolidating tasks.
e.g. Specialized Clerks, DispatchersExplore representative career cohorts that illustrate how AI exposure interacts with real-world barriers.
Substantial cognitive and documentation tasks overlap with AI, but statutory accountability, physical constraints, or institutional regulation buffer structural reduction.
Standardized, screen-based transactional workflows facing aggressive commercial automation pressure with few regulatory or physical moats.
Occupations anchored in unconstrained physical environments, fine manual dexterity, tactile diagnostics, and localized human presence.
Occupations where AI task capability overlap is highest relative to actual structural vulnerability (AI Exposure − Replacement Risk score points).
The occupation map plots verified careers across two independent dimensions: AI Exposure (horizontal X-axis) and Replacement Risk (vertical Y-axis). Each point represents one occupation, allowing you to instantly visualize how task-level software capability compares against structural labour-market vulnerability.
AI Exposure (0–100) measures how much of an occupation's day-to-day task mix overlaps with current AI capabilities. Replacement Risk (0–100) measures structural vulnerability after accounting for real-world friction—including physical constraints, human dependency, fiduciary accountability, adoption economics, and institutional regulations.
A job can be highly exposed to AI without being easy to replace. Occupations such as software developers, nurse practitioners, and financial advisors have high capability overlap with AI for drafting and analysis, yet statutory liability, system architecture, and human bedside care prevent direct headcount reduction.
No. JobsVsAI scores are index ratings on a 0–100 scale, not probabilities or unemployment forecasts. A score of 75 indicates that an occupation exhibits higher relative structural vulnerability compared to lower-scoring occupations across the economy.
This explorer plots our verified cohort of 507 occupations with complete task-level evidence. Preliminary estimates are excluded from the default map to maintain strict methodology and empirical rigor.