Energy Auditors
Construction and Extraction Occupations- O*NET-SOC-Code
- 47-4011.01
Conduct energy audits of buildings, building systems, or process systems. May also conduct investment grade audits of buildings or systems.
Berufsbezeichnungen und Aufgabenbeschreibungen werden wie veröffentlicht auf Englisch angezeigt. Beschriftungen, einschließlich der Aufgabenarten, sind übersetzt.
KI-Exposition
- Datenquelle: BLSVeröffentlicht: 2026-08
Hoch· relativ
NiedrigVier relative BänderSehr hochWert 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
- Datenquelle: AnthropicVeröffentlicht: 2026-03
0.048
0.000Spannweite der hier geführten Werte0.745Wert auf Berufsgruppenebene
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
- Datenquelle: ILOVeröffentlicht: 2025
0.28
0.09Spannweite der hier geführten Werte0.70Wert 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
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)
21 bewertete Aufgaben · 18 Aufgaben mit β ≥ 0,5 (85.7%)
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.
| Aufgabe | Art | β (OpenAI) |
|---|---|---|
| Measure energy usage with devices such as data loggers, universal data recorders, light meters, sling psychrometers, psychrometric charts, flue gas analyzers, amp probes, watt meters, volt meters, thermometers, or utility meters. | Kern | 0 |
| Perform tests such as blower-door tests to locate air leaks. | Kern | 0 |
| Inspect or evaluate building envelopes, mechanical systems, electrical systems, or process systems to determine the energy consumption of each system. | Kern | 0,5 |
| Prepare audit reports containing energy analysis results or recommendations for energy cost savings. | Kern | 0,5 |
| Analyze energy bills, including utility rates or tariffs, to gather historical energy usage data. | Kern | 0,5 |
| Analyze technical feasibility of energy-saving measures, using knowledge of engineering, energy production, energy use, construction, maintenance, system operation, or process systems. | Kern | 0,5 |
| Calculate potential for energy savings. | Kern | 0,5 |
| Collect and analyze field data related to energy usage. | Kern | 0,5 |
| Compare existing energy consumption levels to normative data. | Kern | 0,5 |
| Determine patterns of building use to show annual or monthly needs for heating, cooling, lighting, or other energy needs. | Kern | 0,5 |
| Educate customers on energy efficiency or answer questions on topics such as the costs of running household appliances or the selection of energy-efficient appliances. | Kern | 0,5 |
| Identify and prioritize energy-saving measures. | Kern | 0,5 |
| Identify opportunities to improve the operation, maintenance, or energy efficiency of building or process systems. | Kern | 0,5 |
| Quantify energy consumption to establish baselines for energy use or need. | Kern | 0,5 |
| Oversee installation of equipment such as water heater wraps, pipe insulation, weatherstripping, door sweeps, or low-flow showerheads to improve energy efficiency. | Kern | 0 |
| Prepare job specification sheets for home energy improvements, such as attic insulation, window retrofits, or heating system upgrades. | Kern | 0,5 |
| Recommend energy-efficient technologies or alternate energy sources. | Kern | 0,5 |
| Examine commercial sites to determine the feasibility of installing equipment that allows building management systems to reduce electricity consumption during peak demand periods. | Kern | 0,5 |
| Identify any health or safety issues related to planned weatherization projects. | Kern | 0,5 |
| Inspect newly installed energy-efficient equipment to ensure that it was installed properly and is performing according to specifications. | Kern | 0,5 |
| Verify income eligibility of participants in publicly financed weatherization programs. | Ergänzend | 0,5 |
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: 47-4011.01 Energy Auditors
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.