Research coverage

Entry-pathway coverage

Official National Careers Service source for England. The complete index of737 source titles was matched against all3039 catalog occupations.

Entry-pathway lists: 324; unambiguously linked ESCO occupations: 306. 2733 occupations lack a usable unambiguous link; this source is not assigned to262 other geographies. The full catalog is retained.

These are current entry pathways and study-subject examples. They do not establish personal eligibility, duration, cost or program availability in2030/2035.

Map view coverage

The main map has 1,598,514 assessments, including 696,112 editorial estimates for gaps.

Missing occupation inputs use a related ISCO median. Missing country inputs use the parent country when available or the international median. The country card shows the chosen inputs.

Each view retains the full catalog. Combined estimates require both components; absence of one is not low risk.

View	Estimates	Missing
GenAI	864,948	733,566
Robotics	163,086	1,435,428
AI + robotics	125,632	1,472,882

The combined index is the larger prepared AI or robotics index. Multiple occupation mappings use the upper alternative for colour, with the range retained. Fixed editorial cutpoints: 5, 15, 30, 50; adoption alternatives and ±20% band shifts are checked. These guides support comparison and learning exploration, not dismissal probabilities.

Physical-task context

Published robot capability scores, US 2026. Official ESCO–O*NET URI mapping was checked for every catalog occupation.

With source context: 2471 / 3039. Explicit mapping/source gaps: 568. Native O*NET scores: 923.

This historical layer does not add country-year forecasts. The map shows the separate GenAI outlook. Where available, robotics scenarios are counted separately below; total automation risk and actual hour losses are not established.

Separate robotics scenarios

Countries: 33 · Prepared numeric classes and years: 35970.

Occupation-country-year values: 163086; explicit missing states: 1435428. These are a separate channel, not extra unique people or jobs.

2022 enterprise-use baselines and US2026 capabilities with editorial growth assumptions (odds doubling in5years; alternatives10/3). Mapping ranges stay separate, without averaging or a claim of empirical calibration.

Indicative GenAI scenario with site assumptions. It does not predict personal dismissal; robotics and other automation are not included.

Catalog coverage and research coverage are counted separately.

Catalogs and assessments

indicative-public-2026-11-05-v3
Occupations	3,039
Countries and territories	263
GenAI component estimates	864,948 / 1,598,514
Missing GenAI component estimates	733,566
Territories available through the list	11

A complete catalog does not establish a complete risk model. An unknown assessment is not zero or low risk. Source observations and forecasts are counted separately.

Every geography, including list-only territories

Technical coverage fields and manifest

release_id: indicative-public-2026-11-05-v3
occupations: 3039
jurisdictions: 263
geometry_features: 258
editorial_map: [object Object]
list_only: BES, BVT, CCK, CXR, GLP, GUF, MTQ, MYT, REU, SJM, TKL
total_cells: 1598514
existing: 864948
missing: 733566
observations: 2102

All list-only territories remain selectable. Boundary conventions reflect Natural Earth and do not assert sovereignty.

{
  "technology_views": {
    "genai": {
      "missing": 733566,
      "existing": 864948,
      "by_category": {
        "low": 397391,
        "high": 84334,
        "minimal": 63275,
        "missing": 733566,
        "moderate": 317468,
        "very_high": 2480
      }
    },
    "combined": {
      "missing": 1472882,
      "existing": 125632,
      "by_category": {
        "low": 37734,
        "high": 26295,
        "minimal": 293,
        "missing": 1472882,
        "moderate": 60296,
        "very_high": 1014
      }
    },
    "robotics": {
      "missing": 1435428,
      "existing": 163086,
      "by_category": {
        "low": 38625,
        "high": 25,
        "minimal": 122398,
        "missing": 1435428,
        "moderate": 2038,
        "very_high": 0
      }
    }
  },
  "robotics_scenarios": {
    "method_version": "robot-indicative-outlook-v1",
    "prepared_values": 35970,
    "countries": 33,
    "existing": 163086,
    "missing": 1435428
  },
  "robotics": {
    "profiles": 3039,
    "with_context": 2471,
    "missing": 568,
    "native_occupations": 923,
    "purpose": "US_2026_capability_context_not_future_risk"
  },
  "career": {
    "entry_route_profiles": 324,
    "entry_route_occupations": 306,
    "skill_profiles": 3039,
    "historical_market_records": 4156,
    "current_requirement_records": 326,
    "published_transition_records": 0,
    "purpose": "classification_overlap_and_scoped_local_context"
  },
  "work_surveys": {
    "profiles": 12,
    "jurisdictions": 1,
    "purpose": "descriptive_self_reported_work_time_only"
  },
  "joint_workload": {
    "systems": 55,
    "usable": 51,
    "suppressed": 4,
    "jurisdictions": 53,
    "purpose": "descriptive_joint_cohort_only"
  },
  "time_evidence": {
    "records": 13,
    "by_country": {
      "GBR": 6,
      "JPN": 4,
      "USA": 1,
      "unknown": 2
    },
    "by_analysis": {
      "sensitivity": 6,
      "primary": 6,
      "secondary": 1
    }
  },
  "country_parameters": {
    "records": 232,
    "jurisdictions": 154,
    "by_horizon": {
      "2030": 4,
      "2035": 4,
      "historical": 224
    },
    "by_identification": {
      "point": 224,
      "bounded": 5,
      "uninformative": 3
    },
    "by_layer": {
      "adoption": 230,
      "reported_time_savings": 2
    }
  },
  "records_by_kind": {
    "claims": 4708,
    "claim_sources": 5097,
    "crosswalks": 4207,
    "gaps": 3767,
    "jurisdiction_requirements": 326,
    "labour_market_assessments": 4156,
    "metrics": 25,
    "observations": 2102,
    "research_parameters": 232,
    "scenario_inputs": 161214,
    "skill_profiles": 3039,
    "snapshots": 435,
    "source_projections": 2940,
    "sources": 349,
    "technology_profiles": 3039,
    "workforce_profiles": 55,
    "work_surveys": 12
  },
  "missing_by_reason": {
    "source_not_available": 705048,
    "insufficient_detail": 28518
  },
  "observations_by_metric": {
    "eef-reported-preparation-time-ratio": 6,
    "epoch-paired-higher-current-bin": 37,
    "epoch-paired-lower-current-bin": 37,
    "epoch-paired-same-bin-not-zero-change": 37,
    "eurostat-robot-firm-use-2022": 40,
    "ilo-genai-task-mean-2025": 427,
    "microsoft-genai-population-use": 588,
    "robot-exposure-index-0-3-2026": 923,
    "time-log_time_ratio": 1,
    "time-minutes_per_note": 1,
    "time-percent_change_in_task_duration": 1,
    "time-seconds_per_document": 4
  },
  "sources": 349,
  "snapshots": 435,
  "source_projections_by_horizon": {
    "2030": 381,
    "2035": 2559
  },
  "exposure_occupations_with_group_context": 2956,
  "exposure_occupations_with_usable_index": 2942,
  "observations_missing_by_reason": {
    "conflicting_evidence": 1,
    "insufficient_detail": 1,
    "insufficient_evidence": 75,
    "source_not_available": 4
  }
}

{
  "status": "published",
  "horizons": [
    2030,
    2035
  ],
  "release_id": "indicative-public-2026-11-05-v3",
  "scenario_id": "baseline",
  "published_at": "2026-11-05T18:34:40.134Z",
  "dataset_class": "research",
  "model_version": "genai-indicative-outlook-v2",
  "schema_version": "1.0.0",
  "catalog_versions": {
    "occupations": "ESCO v1.2.1",
    "jurisdictions": "iso-codes 53b1c294240bcfb7429bbc225b9caeb9bf2128b3; CLDR snapshot; NE ca96624a56bd078437bca8184e78163e5039ad19"
  },
  "catalog_checksums": {
    "occupations": "eed361bc593ee93a45ff493c9ee63e182dca0bbadbf944880f76966bd7dec93b",
    "jurisdictions": "f31cbfb06f545d16ea73334904dd2186b7e334ad2cf923344161d09bf6e9bc09"
  },
  "synthetic_fixture": false,
  "indicative_context": {
    "purpose": "indicative_work_pressure_not_dismissal_probability",
    "baseline_date": "2026-06-30",
    "baseline_year": 2026,
    "horizon_anchor": "year_end",
    "method_version": "genai-indicative-outlook-v2",
    "technology_scope": "genai_only",
    "threshold_policy": "editorial_index_5_15_30_50",
    "growth_assumption": "usage_odds_double_every_3_years",
    "baseline_use_scope": "population_any_purpose_15_64",
    "empirical_calibration": false,
    "source_group_transfer": "ISCO08_group_proxy_for_ESCO",
    "sensitivity_doubling_years": [
      5,
      3,
      2
    ]
  },
  "technology_view_context": {
    "gap_policy": "editorial-genai-gap-v1",
    "combination": "maximum_prepared_component_index",
    "default_view": "auto",
    "mapping_policy": "upper_of_published_mapping_alternatives",
    "method_version": "combined-indicative-view-v1",
    "missing_policy": "require_both_for_combined",
    "empirical_calibration": false
  },
  "robotics_outlook_context": {
    "purpose": "separate_editorial_robotics_scenario",
    "baseline_year": 2022,
    "method_version": "robot-indicative-outlook-v1",
    "capability_year": 2026,
    "empirical_calibration": false
  },
  "technology_view_coverage": {
    "genai": {
      "missing": 733566,
      "existing": 864948,
      "by_category": {
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        "high": 84334,
        "minimal": 63275,
        "missing": 733566,
        "moderate": 317468,
        "very_high": 2480
      }
    },
    "combined": {
      "missing": 1472882,
      "existing": 125632,
      "by_category": {
        "low": 37734,
        "high": 26295,
        "minimal": 293,
        "missing": 1472882,
        "moderate": 60296,
        "very_high": 1014
      }
    },
    "robotics": {
      "missing": 1435428,
      "existing": 163086,
      "by_category": {
        "low": 38625,
        "high": 25,
        "minimal": 122398,
        "missing": 1435428,
        "moderate": 2038,
        "very_high": 0
      }
    }
  }
}