Global AI Impact On Jobs (2010–2025)

🌍 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.

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🌍 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

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🤖 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)

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🧠 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

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📊 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

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📁 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

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⚠️ 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.

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🔄 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.