# The association between national culture and AI readiness: a cross-national study

**Authors:** Kumiko Komatsu, Nina Ždanovič, Masaki Yamabe, Hiroyoshi Iwata, Misa Iwamoto, Shutaro Takeda

PMC · DOI: 10.3389/frai.2026.1727606 · Frontiers in Artificial Intelligence · 2026-02-11

## TL;DR

This study explores how national culture influences a country's readiness to adopt artificial intelligence.

## Contribution

It identifies specific cultural dimensions that are statistically correlated with AI readiness across nations.

## Key findings

- Individualism and Long-Term Orientation are positively correlated with AI readiness.
- Power Distance and Uncertainty Avoidance are negatively correlated with AI readiness.
- Masculinity and Indulgence show no significant relationship with AI readiness.

## Abstract

While the adoption of Artificial Intelligence (AI) is advancing globally, its pace varies significantly across nations. This study statistically examines the associations between Hofstede’s cultural dimensions and national-level AI readiness. A correlation analysis was conducted using data from the Oxford Insights’ “Government AI Readiness Index 2024” and Hofstede’s cultural dimension scores. The findings reveal that Individualism and Long-Term Orientation have a significant positive correlation with AI readiness, whereas Power Distance and Uncertainty Avoidance show a significant negative correlation. Conversely, Masculinity and Indulgence did not have a statistically significant relationship. These results suggest that national cultural characteristics are associated with differences in the adoption of advanced technologies such as AI. To contextualize the statistics, we include an illustrative, non-causal comparison of Japan, the United States, and Singapore.

## Full-text entities

- **Diseases:** AI (MESH:C538142), COVID-19 (MESH:D000086382)

## Full text

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## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12932928/full.md

## References

28 references — full list in the complete paper: https://tomesphere.com/paper/PMC12932928/full.md

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Source: https://tomesphere.com/paper/PMC12932928