Automotive Body and Related Repairers

Installation, Maintenance, and Repair Occupations
O*NET-SOC-Code
49-3021.00

Repair and refinish automotive vehicle bodies and straighten vehicle frames.

Berufsbezeichnungen und Aufgabenbeschreibungen werden wie veröffentlicht auf Englisch angezeigt. Beschriftungen, einschließlich der Aufgabenarten, sind übersetzt.

KI-Exposition

  • Datenquelle: BLSVeröffentlicht: 2026-08

    Niedrig· relativ

    NiedrigVier relative BänderSehr hoch

    Wert auf Berufsgruppenebene

    Skala, Bezugsmenge und Quelle

    Vier relative Bänder (Niedrig / Mittel / Hoch / Sehr hoch)

    831 detaillierte Berufe in der BLS-Beschäftigungsprojektionstabelle. Der Wert wird je Code der National Employment Matrix (NEM) vergeben, daher erhalten Berufe mit demselben NEM-Code dasselbe Band

    Quelldatensatz (XLSX-Download)

  • Datenquelle: AnthropicVeröffentlicht: 2026-03

    0.000

    0.000Spannweite der hier geführten Werte0.745
    Skala, Bezugsmenge und Quelle

    Index der beobachteten Exposition, 0–1 wie veröffentlicht

    Auf O*NET-Aufgaben abgebildet

    Veröffentlicht je SOC-2018-Beruf; jeder O*NET-Beruf mit demselben SOC-2018-Code erhält diesen Wert

    Quelldatensatz (CSV-Download)

  • Datenquelle: ILOVeröffentlicht: 2025

    0.18

    0.09Spannweite der hier geführten Werte0.70

    Wert auf Berufsgruppenebene

    Skala, Bezugsmenge und Quelle

    Index der Exposition gegenüber generativer KI, 0–1 wie veröffentlicht

    Veröffentlicht je ISCO-08-Berufsgattung. Mit diesem Beruf ganz oder teilweise verknüpft durch Anwendung der Umsteigeschlüssel des U.S. Bureau of Labor Statistics (ISCO-08 zu SOC 2010, SOC 2010 zu SOC 2018) in veröffentlichter Form

    Quelldatensatz (PDF-Download)

Welche Art von Wert diese Quelle veröffentlicht

Die Kategorie von BLS ist ein relativer Rang und kein absolutes Niveau, und sie ist keine eigene Messung: Sie fasst die Perzentilränge des Berufs aus mehreren veröffentlichten Studien in vier Bänder zusammen. Sie ist weder eine Beschäftigungs- oder Lohnprognose noch eine Einführungswahrscheinlichkeit und unterscheidet nicht zwischen Automatisierung und Augmentierung.

KI-Exposition (OpenAI-Rubrik)

25 bewertete Aufgaben · 2 Aufgaben mit β ≥ 0,5 (8.0%)

β = direkte Exposition (E1) + 0,5 × Exposition bei verfügbaren Werkzeugen (E2), gemäß der Definition des Quell-Repositorys.

  • Quelleinheit: Aufgaben aus O*NET 27.2 → Berufscode aus O*NET 31.0
  • Alle bewerteten Aufgaben stehen in der Aufgabenliste von O*NET 31.0.
Quelle
OpenAI "GPTs are GPTs" exposure rubric
Ausgabe
gh-main-0471612
Lizenz
MIT License, Copyright (c) 2024 OpenAI

Aufgaben

Aufgabenbeschreibungen aus der O*NET® 31.0 Database, Kernaufgaben zuerst.

AufgabeArtβ (OpenAI)
File, grind, sand, and smooth filled or repaired surfaces, using power tools and hand tools.Kern0
Sand body areas to be painted and cover bumpers, windows, and trim with masking tape or paper to protect them from the paint.Kern0
Follow supervisors' instructions as to which parts to restore or replace and how much time the job should take.Kern0
Remove damaged sections of vehicles using metal-cutting guns, air grinders and wrenches, and install replacement parts using wrenches or welding equipment.Kern0
Cut and tape plastic separating film to outside repair areas to avoid damaging surrounding surfaces during repair procedure and remove tape and wash surfaces after repairs are complete.Kern0
Prime and paint repaired surfaces, using paint sprayguns and motorized sanders.Kern0
Mix polyester resins and hardeners to be used in restoring damaged areas.Kern0
Chain or clamp frames and sections to alignment machines that use hydraulic pressure to align damaged components.Kern0
Fill small dents that cannot be worked out with plastic or solder.Kern0
Fit and weld replacement parts into place, using wrenches and welding equipment, and grind down welds to smooth them, using power grinders and other tools.Kern0
Position dolly blocks against surfaces of dented areas and beat opposite surfaces to remove dents, using hammers.Kern0
Remove damaged panels, and identify the family and properties of the plastic used on a vehicle.Kern0,5
Review damage reports, prepare or review repair cost estimates, and plan work to be performed.Kern0,5
Remove small pits and dimples in body metal, using pick hammers and punches.Kern0
Remove upholstery, accessories, electrical window-and-seat-operating equipment, and trim to gain access to vehicle bodies and fenders.Kern0
Clean work areas, using air hoses, to remove damaged material and discarded fiberglass strips used in repair procedures.Kern0
Adjust or align headlights, wheels, and brake systems.Kern0
Apply heat to plastic panels, using hot-air welding guns or immersion in hot water, and press the softened panels back into shape by hand.Kern0
Soak fiberglass matting in resin mixtures and apply layers of matting over repair areas to specified thicknesses.Kern0
Fit and secure windows, vinyl roofs, and metal trim to vehicle bodies, using caulking guns, adhesive brushes, and mallets.Kern0
Replace damaged glass on vehicles.Kern0
Inspect repaired vehicles for proper functioning, completion of work, dimensional accuracy, and overall appearance of paint job, and test-drive vehicles to ensure proper alignment and handling.Kern0
Cut openings in vehicle bodies for the installation of customized windows, using templates and power shears or chisels.Ergänzend0
Read specifications or confer with customers to determine the desired custom modifications for altering the appearance of vehicles.Ergänzend0
Measure and mark vinyl material and cut material to size for roof installation, using rules, straightedges, and hand shears.Ergänzend0

Berufsinformationen

Quellen und Namensnennung

This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.

Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.

O*NET OnLine: 49-3021.00 Automotive Body and Related Repairers

KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.

Vollständige Namensnennung und Lizenzen