KPMG AI Index shows: USA dominates the race for AI

New KPMG study systematically compares the AI performance of major economies for the first time:

• The US is clearly ahead in all areas of the global AI comparison
• Despite good conditions, Europe and Germany lag behind in rapid AI scaling
• China is strong in patents, but lower international cooperation is hampering AI scaling
• Study sees great opportunity for Europe to strengthen technological sovereignty, reduce dependencies, and scale AI rapidly without abandoning responsible standards

Berlin, January 21st 2026

The United States is clearly leading the global race for artificial intelligence. Europe follows closely behind China, but despite their technological, industrial, and scientific strengths, neither economy can currently keep pace with the economic momentum of the US. This is shown by a study conducted by KPMG in Germany in collaboration with the German AI Association, for which over 900 decision-makers from business, technology, and politics worldwide were surveyed and extensive data was evaluated.

The analysis is based on the Strategic AI Capability Index (SACI), which KPMG developed in collaboration with the economic research institute Oxford Economics. It measures the extent to which AI is already being used in the economy, the viability of political and legal frameworks, and the strength of research, skilled workers, and training in the economies. 

In the overall results, the US is clearly in the lead with 75.2 points on a scale of zero to 100. This lead is based on the rapid and widespread use of AI in companies. Liquid capital markets and broad access to computing capacity enable companies to move AI applications more quickly from the experimental phase to operational use. The broad economic use also coincides with a strong research landscape with many well-trained talents. Overall, the US relies on a strong infrastructure that allows the use of AI to be scaled quickly and efficiently. 

Europe achieved an overall score of 48.8 points, placing it well behind the US. The continent has a strong industrial base in certain sectors and expertise in areas such as regulation, governance, and specific areas of research. However, these have had only a limited economic impact so far. The introduction of AI in companies is progressing more slowly, with many applications stuck in the pilot stage. High energy prices, limited computing power, and fragmented capital markets are hampering AI scaling. 

China achieved an overall score of 48.2 points, placing it just behind Europe. The country has strong industrial strengths, high patent activity, and extensive control over key hardware components. Nevertheless, AI has so far only been used to a limited extent in the economy. Many companies use AI selectively, so productivity gains remain rare. Low international networking also hinders AI scaling and knowledge exchange.

The index shows considerable differences within Europe. The United Kingdom and Ireland achieve the highest score of 69.2 points and come closest to the US level. The region benefits from high investment momentum, good access to capital, and comparatively rapid implementation of AI in companies. Western Europe follows with 57.1 points, while the DACH region is slightly below with 54 points. Both regions have strong industrial and research structures, but are only making gradual progress in terms of scaling and productivity gains. Northern, Southern, and Central and Eastern Europe are lagging further behind. Northern Europe scores 41.3 points, placing it in the lower midfield. Southern Europe, with 26.3 points, and Central and Eastern Europe, with 28.8 points, perform significantly weaker. In these regions, limited access to capital, weaker infrastructure, and low application depth are the main factors slowing down the development of AI on an industrial scale.

The results clearly show that Europe must strengthen its technological competitiveness and sovereignty. 

According to the study, measures with high leverage include the rapid establishment of a European computing capacity reserve for start-ups and growth companies, significantly accelerated funding procedures with short decision-making cycles, and the mobilization of growth capital, for example through the greater involvement of institutional investors and modernized investment models. In addition, targeted programs are needed to accelerate industrial AI applications – especially in small and medium-sized enterprises – expand the talent pool through training and easier immigration, and strengthen European autonomy and independence in security-related AI. Sustainability can become a specific locational advantage, for example through energy-efficient AI infrastructure and clear framework conditions for "green AI."