Individualism and long-term vision drive higher AI readiness across nations

The global race to adopt artificial intelligence (AI) technologies is accelerating, but not all countries are moving at the same speed. Differences in infrastructure and policy only partly explain the gap, prompting researchers to look deeper into structural and societal factors that shape national innovation capacity.

The study The association between national culture and AI readiness: a cross-national study, published in Frontiers in Artificial Intelligence, investigates whether national culture plays a measurable role in AI preparedness. The research links Hofstede’s cultural dimensions to the Government AI Readiness Index across 61 countries.

The researchers pose a direct question: beyond economic strength and regulatory frameworks, do deep-rooted cultural values help explain why some countries are more prepared for AI than others?

Individualism and long-term vision drive AI readiness

The strongest statistical relationship uncovered in the study concerns Individualism. Countries scoring higher on Hofstede’s Individualism dimension, which reflects the degree to which societies emphasize personal autonomy over collective cohesion, show significantly higher AI readiness scores.

In correlation analysis, Individualism exhibits the strongest positive association with AI readiness. The relationship remains robust even when controlling for other cultural dimensions in multiple regression analysis. In practical terms, societies that reward initiative, entrepreneurial experimentation and decentralized decision-making appear better positioned to develop and implement AI systems at scale.

The researchers link this pattern to broader innovation literature. More individualistic cultures tend to encourage risk-taking and novel problem-solving, traits that align with rapid adoption of emerging technologies. AI ecosystems in such countries often feature agile startups, venture capital activity and decentralized research networks.

Long-Term Orientation emerges as the second major positive driver. This cultural dimension reflects a society’s emphasis on future rewards, perseverance and long-term planning rather than short-term gratification. Countries scoring higher in Long-Term Orientation also show significantly higher AI readiness.

The connection is intuitive. AI deployment requires sustained investment in education, infrastructure and regulatory capacity. Societies that prioritize long-term development may be more willing to allocate resources toward future technological capability rather than immediate returns.

When both Individualism and Long-Term Orientation are included in regression models, they remain the only statistically significant predictors among the six cultural dimensions. This suggests that autonomy and forward-looking planning may be particularly influential cultural enablers of AI preparedness at the national level.

Hierarchy and risk aversion slow adoption

While two cultural dimensions show positive associations, two others demonstrate the opposite effect. Power Distance and Uncertainty Avoidance are both negatively correlated with national AI readiness.

Power Distance measures the extent to which societies accept hierarchical authority and unequal power distribution. Countries with higher Power Distance scores tend to exhibit lower AI readiness levels in the study’s analysis. The researchers suggest that highly centralized authority structures may limit open communication, decentralized experimentation and information sharing, all of which are important for large-scale AI implementation.

In high Power Distance contexts, innovation decisions may be concentrated within rigid bureaucratic hierarchies. This structure can slow adoption of disruptive technologies that require cross-sector collaboration and rapid adaptation.

Uncertainty Avoidance, which captures a society’s tolerance for ambiguity and risk, also shows a significant negative association with AI readiness. Countries that score high on Uncertainty Avoidance often prefer stability, clear rules and established routines. AI systems, especially generative AI technologies, introduce ambiguity, ethical complexity and regulatory uncertainty. In cultures less comfortable with risk and experimentation, this may slow deployment.

The negative relationship does not imply that risk-averse societies reject AI outright. Rather, they may adopt more cautious and incremental approaches, emphasizing regulatory safeguards and careful evaluation before scaling implementation.

Two cultural dimensions, Masculinity and Indulgence, do not demonstrate statistically significant relationships with AI readiness. Masculinity reflects competitiveness and achievement orientation, while Indulgence captures attitudes toward gratification versus restraint. The absence of significant associations suggests that competitiveness or pleasure-seeking behavior may not meaningfully shape national preparedness for AI.

Taken together, the pattern across the four significant dimensions forms a coherent narrative. Societies that value autonomy and long-term planning tend to exhibit higher AI readiness. Societies characterized by strong hierarchical authority and discomfort with uncertainty tend to show lower readiness levels.

Data, method and cross-national patterns

The study is based on publicly available country-level data from two sources. The dependent variable, AI readiness, comes from the Government AI Readiness Index 2024. This index evaluates how prepared governments are to implement AI in public services and aggregates 40 indicators into an overall readiness score on a scale of zero to 100.

The independent variables are Hofstede’s six national cultural dimensions: Individualism, Power Distance, Masculinity, Uncertainty Avoidance, Long-Term Orientation and Indulgence. Each dimension is measured on a standardized scale from zero to 100.

The final sample includes 61 countries for which complete data were available across both datasets. Countries missing either AI readiness scores or any cultural dimension score were excluded. The analysis relies on complete-case data and does not employ imputation.

Researchers conducted Pearson correlation analysis to assess bivariate relationships and then applied multiple linear regression to examine the relative contribution of each cultural dimension when modeled simultaneously. The overall regression model is statistically significant and explains more than half of the variance in AI readiness scores across countries.

Although some cultural dimensions show significant correlations in isolation, only Individualism and Long-Term Orientation remain significant predictors when all six dimensions are included together. The researchers note that Hofstede’s dimensions are intercorrelated, meaning shared variance can affect statistical significance in multivariate models.

The authors note that their findings reflect statistical associations rather than causal relationships. The data are cross-sectional and rely on secondary indices. Cultural dimensions may interact with economic, institutional and infrastructural variables not fully captured in the model.

United States, Singapore and Japan: Different paths to readiness

To contextualize their statistical findings, the researchers include an illustrative comparison of three high-scoring countries: the United States, Singapore and Japan.

The United States ranks first in AI readiness. It combines very high Individualism with relatively low Power Distance. This cultural configuration aligns with a decentralized innovation ecosystem characterized by entrepreneurial experimentation, venture-backed startups and competitive technology markets.

Singapore ranks second in AI readiness but presents a contrasting cultural profile. It scores low on Individualism and high on Power Distance, yet also exhibits high Long-Term Orientation. Rather than relying on bottom-up experimentation, Singapore has pursued a coordinated, state-led AI strategy. Strong government planning, regulatory frameworks and institutional support mechanisms have propelled its AI development.

Japan ranks lower than the United States and Singapore but still performs strongly overall. It combines high Long-Term Orientation with higher Uncertainty Avoidance. The country is often characterized by cautious but meticulous technology implementation, emphasizing governance frameworks and incremental progress.

These cases demonstrate that high AI readiness is not tied to a single cultural blueprint. Distinct cultural profiles can support different models of AI adoption. What matters, the study suggests, is alignment between cultural traits and policy design.

Strategic implications for AI policy

In societies with high Individualism, policies that encourage entrepreneurial innovation and decentralized experimentation may gain traction more easily. In societies with strong Long-Term Orientation, sustained investment strategies may align well with cultural expectations.

On the other hand, in high Power Distance contexts, centralized implementation models may be more effective than decentralized ones. In high Uncertainty Avoidance societies, transparent governance frameworks and regulatory clarity may be essential to build trust in AI systems.

The researchers acknowledge several limitations. The study uses cross-sectional country-level data and cannot establish causation. The sample is restricted to countries with complete data coverage, which may introduce selection bias. Both the AI Readiness Index and Hofstede scores are secondary measures with inherent assumptions.

AI readiness is not solely a function of GDP, digital infrastructure or regulatory ambition. Deep-rooted cultural orientations are statistically associated with how prepared countries are to adopt and implement artificial intelligence in the public sector.