Isle of Man Job Market
Live market intelligence from 573 active vacancies
Jobs by Occupation (SOC2020 major group)
Based on 573 AI-enriched vacancies.
Jobs by Area
Employer Type
Automation Risk
AIOE measures generative AI augmentation potential per role (Eloundou et al., 2023). Counts shown as number of enriched jobs (% of all active vacancies).
Automation Risk — Public Sector vs Private / Agency
Distribution of automation risk bands across employer types. Public sector = jobs classified as government/public authority. Private / Agency = direct hire and agency-placed roles.
Most In-Demand Skills
Based on 573 AI-enriched jobs. Click any skill to filter live vacancies.
Top Knowledge Areas in Demand
Most frequently required knowledge domains across active IOM vacancies, derived from our canonical knowledge taxonomy.
Task Automation Breakdown
Classification of individual tasks across AI-enriched vacancies: routine (automatable), augmented (AI-assisted human work), and human (resistant to automation). Based on O*NET task decomposition and GPT-4o analysis.
Total tasks analysed: 4,885 across 573 enriched vacancies. Human and augmented tasks represent the automation-resilient portion of IOM's workforce profile.
O*NET Occupational Insights
🔥 Hot Technologies in Demand
Technologies flagged as emerging / high-demand by O*NET across AI-enriched IOM vacancies.
AI Exposure by Occupational Group
Average AI exposure (AIOE) and automation risk across SOC2020 major occupational groups, derived from 573 AI-classified IOM vacancies.
Radar — AIOE & Risk by Occupation
Each axis = a SOC major group. Outer = higher exposure. Blue = AI exposure (AIOE), pink = automation risk.
Scatter — AIOE vs Automation Risk
Each dot = one enriched vacancy. Hover for job details. Dashed lines at 33 % and 66 % risk. Colour = employer type.
AI Capability vs Adoption
Top 8 occupational categories. Orange = observed adoption, blue = unexploited potential.
Bubble — All vacancies
SOC sub-major groups. X = AIOE, Y = risk, size = IOM vacancies.
Bubble size = number of IOM vacancies in that occupational group. Based on 573 enriched jobs.
Bubble — Public sector
SOC sub-major groups, public sector employers only.
Bubble size = number of IOM vacancies in that occupational group. Based on 99 enriched jobs.
Bubble — Direct hire & Agency
SOC sub-major groups, private employers and recruitment agencies.
Bubble size = number of IOM vacancies in that occupational group. Based on 468 enriched jobs.
AI Capability & Deployment Research
Comparing theoretical AI capability with observed adoption rates across occupational categories, and the resulting deployment opportunity gaps.
AI Capability vs Observed AI Adoption — by Occupational Category
Top 8 categories. Stacked bars: orange = current observed AI adoption; blue = unexploited AI potential (capability − observed). Hover to see IOM vacancy count. Based on Eloundou et al. (GPTs are GPTs, 2023).
AI Deployment Opportunity Gap — by SOC Major Group
Difference between theoretical AI capability and observed adoption (capability − observed). Larger = more untapped AI potential. Dashed line at 50%. Averaged across research categories per SOC group.
IOM Vacancies by Occupational Category
Top 8 categories by vacancy count, mapped from SOC2020 major groups. SOC groups spanning multiple categories have their count distributed evenly.
UK SOC2020 Occupational Breakdown
Job counts by Standard Occupational Classification, based on 573 AI-classified vacancies.
Major Groups (1-digit SOC)
Sub-Major Groups (2-digit SOC)
Unit Groups (4-digit SOC) — Top 30
This site incorporates information from O*NET Web Services by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). O*NET® is a trademark of USDOL/ETA. Occupational data (tasks, skills, knowledge, abilities, interests, career clusters, Bright Outlook designations, and hot technologies) is sourced from O*NET Online and used to enrich IOM job listings with AI-powered career intelligence.