Loss Prevention Managers
Management Occupations- رمز O*NET-SOC
- 11-9199.08
Plan and direct policies, procedures, or systems to prevent the loss of assets. Determine risk exposure or potential liability, and develop risk control measures.
تُعرض أسماء المهن وأوصاف المهام بالإنجليزية كما نُشرت. أما التسميات، ومنها أنواع المهام، فمترجمة.
التعرّض للذكاء الاصطناعي
- مصدر البيانات: BLSتاريخ النشر: 2026-08
مرتفع· نسبي
منخفضأربع فئات نسبيةمرتفع جدًاقيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
أربع فئات نسبية (منخفض / متوسط / مرتفع / مرتفع جدًا)
831 مهنة تفصيلية في جدول توقعات التوظيف لدى BLS. وتُسند القيمة على مستوى رمز مصفوفة التوظيف الوطنية (NEM)، فالمهن التي تشترك في الرمز نفسه تأخذ النطاق نفسه
- مصدر البيانات: Anthropicتاريخ النشر: 2026-03
0.069
0.000نطاق القيم المعروضة هنا0.745قيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
مؤشر التعرّض المرصود، 0–1 كما نُشر
مربوط بمهام O*NET
منشورة لكل مهنة في SOC 2018؛ وكل مهنة في O*NET تحمل رمز SOC 2018 نفسه تأخذ هذه القيمة
- مصدر البيانات: ILOتاريخ النشر: 2025
0.32–0.42· 6 مجموعات ISCO-08
المقياس والأساس والمصدر
مؤشر التعرّض للذكاء الاصطناعي التوليدي، 0–1 كما نُشر
قيمة منشورة على مستوى مجموعة الوحدة في ISCO-08. رُبطت بهذه المهنة بتطبيق جداول التناظر الرسمية لمكتب إحصاءات العمل الأمريكي (BLS) (من ISCO-08 إلى SOC 2010، ومن SOC 2010 إلى SOC 2018) كما نُشرت، والتناظر كلي أو جزئي
ما نوع القيمة التي ينشرها هذا المصدر
فئة BLS رتبة نسبية لا مستوى مطلق، وليست قياسًا مباشرًا: فهي تجمع الرتب المئينية للمهنة في عدة دراسات منشورة في أربع فئات. وهي ليست توقّعًا للتوظيف أو الأجور، ولا احتمالًا للتبني، ولا تفرّق بين الأتمتة والتعزيز.
قيمة ILO لكل مجموعة ISCO-08 مرتبطة
- ISCO-08 1114Senior Officials of Special-interest Organizations0.37
- ISCO-08 1213Policy and Planning Managers0.36
- ISCO-08 1219Business Services and Administration Managers Not Elsewhere Classified0.42
- ISCO-08 1322Mining Managers0.35
- ISCO-08 1349Professional Services Managers Not Elsewhere Classified0.38
- ISCO-08 1431Sports, Recreation and Cultural Centre Managers0.32
التعرض للذكاء الاصطناعي (معيار OpenAI)
27 مهمة مقيَّمة · 22 مهمة بقيمة β ≥ 0.5 (81.5%)
β = التعرّض المباشر (E1) + 0.5 × التعرّض عند توفر الأدوات (E2)، وفق تعريف المستودع المصدري.
- وحدة المصدر: مهام O*NET 27.2 ← رمز المهنة في O*NET 31.0
- جميع المهام المقيَّمة موجودة في قائمة مهام O*NET 31.0.
- المصدر
- OpenAI "GPTs are GPTs" exposure rubric
- الإصدار
- gh-main-0471612
- الترخيص
- MIT License, Copyright (c) 2024 OpenAI
المهام
أوصاف المهام من O*NET® 31.0 Database، والمهام الأساسية أولًا.
| المهمة | النوع | β (OpenAI) |
|---|---|---|
| Review loss prevention exception reports and cash discrepancies to ensure adherence to guidelines. | أساسية | 0.5 |
| Perform cash audits and deposit investigations to fully account for store cash. | أساسية | 0.5 |
| Provide recommendations and solutions in crisis situations such as workplace violence, protests, and demonstrations. | أساسية | 0.5 |
| Monitor and review paperwork procedures and systems to prevent error-related shortages. | أساسية | 0.5 |
| Investigate or interview individuals suspected of shoplifting or internal theft. | أساسية | 0 |
| Direct installation of covert surveillance equipment, such as security cameras. | أساسية | 0.5 |
| Advise retail establishments on development of loss-investigation procedures. | أساسية | 0.5 |
| Visit stores to ensure compliance with company policies and procedures. | أساسية | 0 |
| Verify correct use and maintenance of physical security systems, such as closed-circuit television, merchandise tags, and burglar alarms. | أساسية | 0.5 |
| Train loss prevention staff, retail managers, or store employees on loss control and prevention measures. | أساسية | 0 |
| Supervise surveillance, detection, or criminal processing related to theft and criminal cases. | أساسية | 0.5 |
| Recommend improvements in loss prevention programs, staffing, scheduling, or training. | أساسية | 0.5 |
| Perform or direct inventory investigations in response to shrink results outside of acceptable ranges. | أساسية | 0.5 |
| Hire or supervise loss prevention staff. | أساسية | 0 |
| Maintain documentation of all loss prevention activity. | أساسية | 1 |
| Coordinate theft and fraud investigations involving career criminals or organized group activities. | أساسية | 0.5 |
| Direct loss prevention audit programs including target store audits, maintenance audits, safety audits, or electronic article surveillance (EAS) audits. | أساسية | 0.5 |
| Develop and maintain partnerships with federal, state, or local law enforcement agencies or members of the retail loss prevention community. | أساسية | 0 |
| Coordinate or conduct internal investigations of problems such as employee theft and violations of corporate loss prevention policies. | أساسية | 0.5 |
| Collaborate with law enforcement to investigate and solve external theft or fraud cases. | أساسية | 0.5 |
| Assess security needs across locations to ensure proper deployment of loss prevention resources, such as staff and technology. | أساسية | 0.5 |
| Analyze retail data to identify current or emerging trends in theft or fraud. | أساسية | 0.5 |
| Advise retail managers on compliance with applicable codes, laws, regulations, or standards. | أساسية | 0.5 |
| Monitor compliance to operational, safety, or inventory control procedures, including physical security standards. | أساسية | 0.5 |
| Identify potential for loss and develop strategies to eliminate it. | أساسية | 0.5 |
| Administer systems and programs to reduce loss, maintain inventory control, or increase safety. | أساسية | 0.5 |
| Maintain databases such as bad check logs, reports on multiple offenders, and alarm activation lists. | تكميلية | 1 |
معلومات مهنية
المصادر والإسناد
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: 11-9199.08 Loss Prevention Managers
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.