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Global AI Impact On Jobs (2010–2025)

@kaggle.sarcasmos_ai_society

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How AI reshaped jobs, skills, salaries, and automation risk across 80+ countries

🌍 Global AI Impact on Jobs (2010–2025)

📌 Context

Artificial Intelligence has rapidly transformed how work is performed, what skills are demanded, and how wages evolve across industries and regions. However, globally consistent job-level datasets that track AI adoption over time are rare.

This dataset was created to bridge that gap by providing a globally representative, job-level view of AI’s impact on employment from 2010 to 2025.

Each row represents a single job listing, enriched with:

  • AI adoption signals
  • Skill requirements
  • Salary dynamics
  • Automation and displacement risk
  • Industry-level AI maturity

The dataset is fully synthetic but grounded in real-world labor market trends, making it suitable for research, education, and machine learning experimentation.


🌍 Coverage

  • Time range: 2010–2025
  • Geography: 80+ countries across all major world regions
  • Industries: Tech, Finance, Healthcare, Manufacturing, Education, Retail, Energy, Government, Agriculture
  • Company sizes: Startup, Small, Medium, Large, Enterprise

🤖 AI Signals Included

  • Explicit AI mentions in job listings
  • AI keyword evolution (Machine Learning → Deep Learning → LLMs & Generative AI)
  • AI intensity score indicating how central AI is to each role
  • Industry-level AI adoption stage (Emerging, Growing, Mature)

🧠 Key Features

  • Job title, seniority, industry, and company size
  • Core skills and AI-specific skills
  • Salary (USD) with year-over-year change
  • Automation risk and reskilling indicators
  • Precomputed embedding cluster IDs for analytics and clustering

📊 Example Use Cases

This dataset supports a wide range of analytical and machine learning tasks:

  • Time-series analysis: Track AI job growth before and after key inflection points
  • Clustering: Group jobs by AI intensity and skill composition
  • Classification: Predict AI adoption or automation risk
  • Salary modeling: Quantify AI wage premiums across regions
  • Societal impact analysis: Identify roles at high displacement risk
  • Feature engineering practice: Multi-signal tabular modeling

📁 File Information

ai_impact_jobs_2010_2025.csv

Main dataset containing 5,000 job listings with AI adoption signals, skills, salary dynamics, and societal risk indicators.

Selected columns:

  • posting_year – Year the job was posted
  • country, region, city – Geographic attributes
  • industry, company_size, seniority_level – Job context
  • ai_mentioned, ai_keywords, ai_intensity_score – AI adoption indicators
  • salary_usd, salary_change_vs_prev_year_percent – Compensation dynamics
  • automation_risk_score, ai_job_displacement_risk – Societal impact signals
  • job_description_embedding_cluster – Precomputed cluster ID
  • industry_ai_adoption_stage – Industry AI maturity level

⚠️ Notes

  • This dataset is synthetic and intended for research, education, and modeling practice.
  • Trends are designed to reflect realistic global labor-market dynamics.
  • Salaries are normalized to USD for comparability across countries.

🔄 Update Plan

Planned future updates may include:

  • Extended years beyond 2025
  • Additional countries and industries
  • Job-description text fields
  • Dynamic AI skill embeddings

Community feedback and notebook contributions are welcome.


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