مهندسو موثوقية المواقع
الحاسوب والرياضياتالتعرّض للذكاء الاصطناعي
- مصدر البيانات: BLSتاريخ النشر: 2026-08
مرتفع جدًا· 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
0.311
0.000نطاق القيم المعروضة هنا0.745المقياس والأساس والمصدر
- مصدر البيانات: ILOتاريخ النشر: 2025
0.53
0.09نطاق القيم المعروضة هنا0.70قيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
مؤشر التعرّض للذكاء الاصطناعي التوليدي، 0–1 كما نُشر
وحدة التصنيف ISCO-08 — تأخذ كل المهن ذات الرمز نفسه هذه القيمة
محسوب من قِبل هذا الموقع وليس منشورًا من منظمة العمل الدولية: من بين 1,012 مهنة يربطها هذا الموقع بمجموعة بيانات المنظمة، تبلغ نسبة التي تساوي هذه القيمة أو تتجاوزها 14%.
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.
Task-level exposure
عرض 151 مهمة مخفية| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Search electronic sources, such as databases or repositories, or manual sources for information.15-1299 | 4.950064.0 | 5.720045.1 |
Confer with users to analyze, configure, or troubleshoot applications.15-1299 | 0.64008.3 | 0.15001.2 |
Provide technical guidance or support for the development or troubleshooting of systems.15-1299 | 0.48006.2 | 0.07000.6 |
Write and execute scripts to automate tasks, such as parsing large data files.15-1299 | 0.21002.7 | 0.16001.3 |
Create, analyze, report, convert, or transfer data, using specialized applications program software.15-1299 | 0.15001.9 | 0.24001.9 |
Evaluate existing systems to determine effectiveness, and suggest changes to meet organizational requirements.15-1299 | 0.08001.0 | 0.04000.3 |
Monitor system operation to detect potential problems.15-1299 | 0.07000.9 | 0.67005.3 |
Review existing or incoming data for currency, accuracy, usefulness, quality, or completeness of documentation.15-1299 | 0.06000.8 | 3.560028.1 |
Review or update Web page content or links in a timely manner, using appropriate tools.15-1299 | 0.06000.8 | 0.11000.9 |
Retrieve electronic assets from repository for distribution to users, collecting and returning to repository, if necessary.15-1299 | 0.06000.8 | 0.11000.9 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Submit project deliverables, ensuring adherence to quality standards.O*NET Task ID 16152 | 1.0 |
Initiate, review, or approve modifications to project plans.O*NET Task ID 16159 | 1.0 |
Develop and manage work breakdown structure (WBS) of information technology projects.O*NET Task ID 16171 | 1.0 |
Perform risk assessments to develop response strategies.O*NET Task ID 16151 | 0.5 |
Monitor the performance of project team members, providing and documenting performance feedback.O*NET Task ID 16153 | 0.5 |
Confer with project personnel to identify and resolve problems.O*NET Task ID 16154 | 0.5 |
Assess current or future customer needs and priorities by communicating directly with customers, conducting surveys, or other methods.O*NET Task ID 16155 | 0.5 |
Schedule and facilitate meetings related to information technology projects.O*NET Task ID 16156 | 0.5 |
Monitor or track project milestones and deliverables.O*NET Task ID 16157 | 0.5 |
Negotiate with project stakeholders or suppliers to obtain resources or materials.O*NET Task ID 16158 | 0.5 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
معلومات مهنية
تغيّرات حديثة تخصّ هذه المهنة
يوليو 2026: ADP/Stanford linked postings-payroll study of ~7,000 IT workers (2019-2025) prices tasks separately within IT jobs. Advising others on the design or use of technologies is among 8 higher-wage activities; five tasks lost compensation value in 2023-2025 vs 2019-2022, including "develop models of systems, processes, or products." Effect sizes were not published.
[المصدر: ADP Research / Stanford Digital Economy Lab, Unbundling Jobs (July 2026)]مارس 2026: EIG (Mar 2026) argues the weakness in young adults' labor market is about age, not education: young workers of all education levels lag the rest of the labor market, which does not fit the media narrative of AI displacing computer science majors and entry-level graduates.
[المصدر: EIG: AI and Young-Adult Jobs (March 2026)]مارس 2026: Brookings (Mar 2026) says research on AI and the labor market is still in its first inning, and studies disagree: ADP payroll data show employment fell more for young workers in high-AI-exposure occupations, while CPS data show unemployment rose less for workers in more exposed occupations.
[المصدر: Brookings Institution]These summaries were written by AI Changing Work from the source linked with each one, and any figures in them are given as AI Changing Work summarised them; they can differ from the source's own wording and from figures shown elsewhere on this page, so check the source before relying on them. AI Changing Work matched this page's occupation to an O*NET occupation and chose, by its own judgment, case by case, which summaries relate to that O*NET occupation; a summary appearing here does not mean that its source names this occupation.