This chart compares pillar scores across global regions, showing large differences in overall AI readiness. Europe and Other regions score the highest across most pillars, while Africa and Latin America show much lower and more variable performance.

Through the table, we clearly see that there’s a major difference between each region. For example, North America and Europe have the highest score in all sections and significantly lead the all pillars. The average score for North America Government is 74, the technology section is 61, and the data infrastructure is a high of 84. A similar situation happens in Europe. On the contrary, Africa and parts of the Caribbean/Central America have significantly lower scores. The average government score in Africa is only 31, and the technology industry is only 25. 

Subsequently, we calculated the variance of the three pillars of these regions. The results show that the government pillar has the greatest difference. This result indicates that each region has significant differences in aspects of policy making and regulatory capacity. The next difference is the Data and Infrastructure. This shows that there is a great imbalance in global digital development and research systems. 

In Radu’s article, different countries’ governance models can directly decide whether they can build AI development effectively. This explains the situation that regions with lower government scores also tend to have lower infrastructure scores. GDP, investment in research, and urbanization strongly influence AI development.