Context & overview
AI has become a central driver of innovation in Europe, reshaping economies and job markets. Yet, labour market intelligence on AI often treats AI skills as a single block overlooking the fact that proficiency ranges from basic literacy to cutting-edge research. To fill this gap, the study Solving Europe’s AI Talent Equation, introduced a comparative framework to analyse AI demand and supply across European countries. The research divides AI roles into 3 tiers of expertise, mapping vacancies against available talent, identifying mismatches at both national and continental level.
This study is highly relevant to the AI-VET project because it demonstrates how data-driven skills intelligence can reveal mismatches between training supply and labour market demand.
Challenges addressed
The study sought to overcome three main shortcomings:
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Traditional statistics rarely differentiate between beginner, mid-level and advanced AI roles. |
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Policymakers could not easily identify where shortages or surpluses existed across Europe. |
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Without clarity on skill levels, education systems risk to produce graduates who do not match labour market needs. |
Solution implemented
Researchers proposed a tiered methodology to classify AI skills:
Tier 0 (AI literacy): individuals with basic awareness or the ability to use AI tools.
Tier 1 (mid-level): professionals applying AI and data techniques in technical contexts.
Tier 2 (advanced): experts developing models, algorithms or conducting AI research.
Two complementary datasets were used:
With the comparison of vacancies and profiles across tiers, the study calculated the share of demand and supply per country and the ratio of available talent to open positions.
Impact & results
Around half of AI vacancies and nearly two-third of AI talent fall into Tier 1, showing that Europe’s AI labour market is concentrated at the technical practitioner level.
Demand for Tier 0 and Tier 2 roles exceeds supply. About 29% of vacancies request Tier 0 skills, while only 22% of talent fits this profile. At the advanced end, 24% of vacancies target Tier 2 skills, but only 15% of talent is qualified.
Vacancies for Tier 0 and Tier 2 roles have fewer candidates per position, reflecting greater difficulty in filling these jobs compared with Tier 1.
https://www.interface-eu.org/publications/solving-europes-ai-talent-equation
AI skills taxonomy, labour market mismatch, talent supply and demand, comparative framework, European workforce analysis