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GCRI · مستقبل العمل والمهارات

الأتمتة والوظائف

Automation, robotics and AI take over some tasks, assist others and create new ones. Whether this displaces workers, raises productivity and wages or does both depends on the tasks involved, how firms deploy technology and how institutions support transitions. This page sets out how automation affects jobs, how exposure and impact are measured, and what evidence serves the policymakers, employers and unions responsible.

02السؤال

Automation and jobs: how the risk develops.

AI/robotics impact and job redesign. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

الآلية

Tasks, not whole jobs

Most occupations combine tasks that can be automated with tasks that cannot. Automation reshapes jobs more often than it eliminates them outright.

الآلية

Displacement and reinstatement

Technology displaces labour from some tasks and creates new tasks that need people. Net effects depend on the balance between the two.

الآلية

Productivity gains may not reach wages

If gains accrue mainly to capital owners, automation can raise output while wages stagnate for exposed workers.

الآلية

Transitions are costly for individuals

Displaced workers often face long unemployment or lower pay in new jobs, especially older workers and those in declining regions.

03الأساليب والأدلة

How automation and jobs is modelled, measured and tested.

النموذج وافتراضاته وبياناته وعدم اليقين فيه، بالصورة التي يفحصها بها عالم أو مهندس. وتتبع البنى أساليب منشورة. والقيم المرسومة توضيحية، وليست نتائج.

نموذج النظام

The couplings between the systems in automation and jobs: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.

++−++العملالمجتمعالذكاء الاصطناعيالمجتمعاتالاقتصاد⁨R⁩ معزِّزة⁨B⁩ موازِنة
Causal loop diagram from the page’s systems; signs show the direction of influence. Illustrative structure for a system dynamics or network model, not estimated couplings.
مبادئ FAIR التوجيهية · GO FAIR وFORCE11⁨W3C PROV⁩ · اتحاد الشبكة العالميةإرشادات بشأن المعالجة المتسقة لأوجه عدم اليقين · الهيئة الحكومية الدولية المعنية بتغير المناخبيانات CEOS الجاهزة للتحليل · لجنة سواتل رصد الأرض
05المؤشرات الفرعية

ما الذي يُقاس، ومدى جودة قياسه.

يحمل كل مؤشر وحدته ووتيرته ونوع المصدر الذي يستند إليه ووسم الأدلة الذي ستحمله القيمة. ولا تُعرض أي قيم: فالبرنامج يقدّمها بموجب سلطته الخاصة.

المؤشرالوحدةوتيرة الإصدارنوع المصدرالوسم
Employment in occupations with high automation exposurepercent of employmentلكل تقييمTask-based exposure studiesمُقدَّر
Firms using AI or robotspercent of firmsper surveyBusiness surveysمُبلَّغ عنه
Displaced worker re-employment ratepercent re-employed within a yearper surveyDisplaced worker surveysمُبلَّغ عنه
Wage change after displacementpercentper surveyLinked employer-employee dataمُقدَّر
Labour share of incomeالنسبة المئوية من الناتج المحلي الإجماليسنويالحسابات القوميةمُقدَّر
New job titles emergingالعددسنويOccupational classification updates and job postingsمرصود
06المصادر

من أين تأتي الأدلة.

مجموعات بيانات عامة مسمّاة وسجلات مؤسسية، لكلٍّ منها فئة ترخيصها. ولا تُستخدم المصادر المتاحة بموجب اتفاق إلا وفق شروطها، ولا يُعاد نشرها أبدًا.

المصدرما يقدّمهفئة الترخيص
ILO global studies on generative AI exposureOccupational exposure estimates by country and genderPublic, ILO terms
OECD studies on automation and AI in the labour marketEvidence on exposure and adoptionPublic, OECD terms
US Bureau of Labor Statistics Displaced Worker SurveyOutcomes of displaced workersPublic domain, US government
O*NET occupational task databaseTask content of occupations used in exposure studiesمفتوح، CC BY 4.0
Eurostat enterprise AI and robot use statisticsAdoption by firmsOpen, Eurostat reuse policy
07القرارات

من يقرر، وما الذي تخدمه الأدلة.

Future of Work and Skills prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

من يقررالسؤالالأدلة التي تخدمها هذه الصفحة
Labour ministriesWhich workers and regions need transition supportExposure profiles; displacement evidence
Employers and unionsHow to introduce technology and share gainsAdoption and wage evidence
Training providersWhich skills to build for new tasksEmerging task evidence

المخرجات التي يُنتجها هذا الموضوع

  • Task-based exposure profiles by occupation and group
  • Displacement and re-employment analyses
  • Evaluation designs for transition programmes
  • Evidence notes for social dialogue on technology
08الأسئلة الجوهرية

What researchers ask about automation.

  • Which tasks can current AI and robots perform reliably and at acceptable cost?
  • When does technology substitute for workers and when does it complement them?
  • How are productivity gains shared between firms, workers and consumers?
  • How can jobs be redesigned so people keep meaningful, skilled work?
09الآليات

Displacement, productivity and new work.

Automation has a displacement effect, as machines take over tasks, and a productivity effect, as lower costs raise demand and employment elsewhere. Historically, new tasks and occupations have also emerged, reinstating demand for labour. The balance between these forces determines the net effect on employment and wages.

Industrial robots mainly automate physical, repetitive tasks in manufacturing and logistics. Generative AI reaches cognitive tasks such as drafting, summarising and coding. Evidence from early workplace studies suggests AI assistance can raise productivity, sometimes most for less experienced workers, but effects vary widely by task and implementation. What employers choose to automate, and how, matters as much as technical capability.

10المناهج والبيانات

Evidence on automation and its limits.

  1. 01

    Task exposure measures

    Matching technology capabilities to occupational task descriptions, informed by الذكاء الاصطناعي والتعلم الآلي and robotics and automation. Measures depend on judgements about capability that age quickly.

  2. 02

    Robot adoption studies

    Linking robot installations to local employment and wages with الاقتصاد القياسي. Results differ between countries and periods.

  3. 03

    Workplace experiments

    Randomised or natural experiments in firms adopting AI, using العلوم الاجتماعية والسلوكية. Short-run effects may not reflect long-run change.

  4. 04

    Job redesign case studies

    How organisations reorganise work around new tools. Case studies illustrate possibilities rather than averages.

12Where this page’s references

Where this page’s references lead.

الهيئات والوثائق التي تُقرأ هذه الصفحة في ضوئها. وتتغير الحالات والإصدارات؛ ويقود كل رابط إلى الهيئة المُصدِرة.

14أسئلة

أسئلة وأجوبة.

Will automation cause mass unemployment?
Historically, technology has changed jobs more than it has reduced total employment, but transitions are costly for affected workers. Effects of AI are still uncertain.
What is task-based analysis?
Analysing the effect of technology on work through the specific tasks that make up occupations, rather than treating jobs as wholes.
Who is most exposed to automation?
It depends on the technology. Routine manual tasks were most exposed to robots; generative AI exposes clerical and some professional tasks more.
Is automation exposure the same as job loss?
No. Exposure means some tasks in a job could be automated. Whether jobs are lost depends on costs, demand, regulation and how employers reorganise work.
Does AI help or hurt less experienced workers?
Some early studies find the largest productivity gains for less experienced workers in specific tasks. Whether that persists and translates into pay is not yet known.
Can job redesign prevent displacement?
It can preserve and improve many jobs, especially where workers are involved in the redesign, but it cannot offset every displacement. Transition support remains necessary.
Does the platform advise firms on automation?
No. It publishes research and case studies that firms, unions and governments can use.
التقاريرساهم

ساهم بأدلة من هذه الصفحة.

التقارير is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

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