The EU aims to be competitive in the field of AI in comparison to the US and China as its main global competitors.
In Brief #4: AI Competitiveness – Structural challenges of the EU
In Brief #4 as part of the AI@Work project for the European Employers' Institute (EEI)
Institut der deutschen Wirtschaft (IW)
The EU aims to be competitive in the field of AI in comparison to the US and China as its main global competitors.
Despite existing structural strengths, the EU faces persistent structural challenges by remaining significantly behind the US across most dimensions of AI competitiveness and showing only a mixed performance relative to China.
Structural challenges of the EU
Underperformance in R&D
- The EU lags behind the US and China in developing notable AI models and publishing AI-related research articles.
- In addition, companies in Europe also need significantly more time to adapt already existing innovative AI technologies from other regions and to spread AI innovations within their own domestic markets.
Limited private AI investment
- Private AI investment in the EU is substantially lower than in the US.
- Limited private capital restricts the EU's ability to commercialise AI innovations and thus widens the EU's innovation-to-commercialisation gap, consistent with the findings of the Draghi Report.
Significant gap in AI infrastructure
- The EU lags behind the US in quantity of AI infrastructe (data centre capacity) and quality (access to cutting-edge GPU availability).
- Limited access to advanced and large-scale computing capacity constrains the EU’s ability to scale AI models and applications
In Brief #4: AI Competitiveness – Structural challenges of the EU
In Brief #4 as part of the AI@Work project for the European Employers' Institute (EEI)
Institut der deutschen Wirtschaft (IW)
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