National Culture Steers How Governments Embrace Artificial Intelligence

Why do some governments race ahead with artificial intelligence while others hesitate at the starting line? A new study published in Global Public Policy and Governance offers a striking answer: the winds that carry, or stall, a nation’s AI ambitions may be cultural. Drawing on a panel of 244 country-year observations spanning 2020 to 2023, researchers from Huazhong University of Science and Technology and Tsinghua University show that deep-seated national values, measured through Hofstede’s National Culture Index, significantly shape how ready governments are to adopt AI. The findings suggest that the global AI divide is not merely a story of budgets and bandwidth, but of collective psychology.

The research team, led by Qingyu Gao and colleagues, combined Hofstede’s cultural scores with the Government AI Readiness Index published by Oxford Insights, which evaluates countries across government, technology sector, and data and infrastructure pillars. Because cultural values are time-invariant over the study window, the authors employed a random effects panel model, a standard econometric approach for handling characteristics that do not change over time. The final sample covered 61 countries with complete data on all five cultural dimensions examined: power distance, individualism, uncertainty avoidance, masculinity, and long-term orientation. Control variables included internet usage, government expenditure, GDP per capita, population, and unemployment, with missing values imputed using a random forest algorithm.

Three cultural dimensions emerged as decisive. Masculinity, which reflects a society’s emphasis on competition, assertiveness, and achievement, was negatively associated with government AI adoption, with each unit increase predicting a 0.082 unit decrease in readiness. Uncertainty avoidance, the degree to which societies feel threatened by ambiguity and unpredictability, showed a similar inhibitory effect, reducing readiness by 0.076 units per unit increase. In contrast, long-term orientation, the tendency to prioritize future goals over immediate gratification, was the strongest positive predictor, adding 0.13 units of AI readiness per unit increase and reaching statistical significance at the 0.001 level. Power distance and individualism, by comparison, showed no significant effects.

The masculinity result is perhaps the most counterintuitive. Earlier research on e-government had often found masculinity to be a minor or statistically insignificant factor, and one might expect performance-driven, competitive cultures to leap at technologies promising measurable gains. But the authors argue that AI is fundamentally different from earlier digital upgrades. Successful AI adoption demands long-term investment, cross-domain collaboration, and ethical co-governance, qualities that sit uneasily with a cultural orientation toward immediate, controllable competitive wins. AI also carries risks of bias, inequity, and unintended social consequences, and a governance ethos grounded in cooperation and concern for citizen well-being, characteristic of feminine cultures, appears better suited to managing them.

Uncertainty avoidance operates through a more intuitive channel. AI is a radical innovation that raises ethical dilemmas, regulatory ambiguity, and value conflicts, so governments must tolerate experimentation and learn from trial and error. Societies that prize stability and rules tend to perceive such technologies as risky or disruptive, and their decision makers emphasize control and predictability over bold experimentation. The study’s heterogeneity analysis sharpened this picture: the negative effect of uncertainty avoidance was most pronounced in countries with high internet usage, where mature technological infrastructure lowers perceived reliance on AI while heightening concerns about its potential to disrupt existing security frameworks.

Beyond direct effects, the researchers probed a mediating mechanism using Baron and Kenny’s causal step method, supplemented by Sobel tests. Governance effectiveness, drawn from the World Bank’s Worldwide Governance Indicators and lagged by two years to capture temporal effects, proved to be a key pathway. Masculinity and uncertainty avoidance both significantly reduced governance effectiveness, while long-term orientation enhanced it. Governance effectiveness, in turn, strongly promoted AI adoption. Notably, it fully mediated the relationships between masculinity and AI adoption and between uncertainty avoidance and AI adoption, and partially mediated the long-term orientation pathway. In other words, culture does not simply push governments toward or away from AI; it shapes the institutional quality that makes AI integration feasible in the first place.

The heterogeneity analyses revealed that cultural influence is context-dependent in surprising ways. Stratifying countries by GDP per capita at a 20,000 dollar threshold, the team found that the negative effects of masculinity and uncertainty avoidance were stronger in high-income countries, while the positive effect of long-term orientation was concentrated in low-income countries, where resource constraints make long-term strategic planning essential for rationalizing AI investment. The authors suggest that wealthy nations with robust welfare systems and egalitarian gender roles may find traditional masculine norms of competition and control particularly detrimental, and that their sophisticated technological expectations generate heightened concerns about AI security and privacy.

Employment and connectivity conditions further modulated the picture. In high-unemployment countries, power distance showed a significant negative effect on AI adoption, plausibly because governments preoccupied with joblessness and political stability can use centralized authority to reject disruptive technologies. In low-unemployment countries, individualism and long-term orientation turned significantly positive, while uncertainty avoidance remained a brake. Meanwhile, in low internet usage countries, power distance and long-term orientation showed positive effects, suggesting that nations with limited technical capacity may actually benefit from centralized strategic planning and sustained long-term guidance to jumpstart AI development. A significant positive effect of long-term orientation on AI adoption was observed specifically in the cohort combining low income, low unemployment, and low internet usage.

Methodologically, the study reframes AI adoption as a dynamic, process-oriented phenomenon rather than a binary adopt-or-not decision. By using AI readiness as the dependent variable, the authors align with recent scholarship showing that governments that appear well positioned to adopt AI do not always succeed, and that adoption unfolds across initial, assessment, decision, management, and optimization stages. This operationalization matters because failed AI deployments in the public sector can produce bureaucratic dysfunction or even systemic collapse, as documented in cases such as automated debt recovery systems. Readiness, encompassing tangible resources, human capital, and intangible institutional capacity, captures the preparedness that determines whether AI initiatives take root or wither.

The authors acknowledge limitations. Hofstede’s framework, while widely validated, does not cover all countries, restricting generalizability, and its static scores cannot capture cultural evolution over time. Cross-national regressions also face omitted variable bias, and factors such as religion or legal traditions were not modeled. Still, the practical implications are considerable. Policymakers seeking to accelerate government AI adoption may need culturally adapted strategies: institutional designs that reorient competitive, short-term policy cultures toward long-term strategic development, and governance reforms that build the effectiveness through which cultural values ultimately flow. As AI reshapes public administration worldwide, this study suggests that the most important infrastructure may not be silicon, but shared values.

Subject of Research: The influence of Hofstede's national culture dimensions on government artificial intelligence adoption across countries

Article Title: Sailing with the cultural winds: the impact of National culture on government AI adoption

Article References: Gao, Q., Wang, S., Liang, Z., Wang, G., & Guo, L. (2025). Sailing with the cultural winds: the impact of National culture on government AI adoption. Global Public Policy and Governance, 5(3), 251-273. https://doi.org/10.1007/s43508-025-00122-y

Image Credits: AI Generated

DOI: 10.1007/s43508-025-00122-y

Keywords: artificial intelligence, government AI adoption, national culture, Hofstede, AI readiness, governance effectiveness, public sector innovation, uncertainty avoidance, long-term orientation, cross-national study, e-government, public policy