Introduction

This report analyzes global AI adoption trends, investment levels, automation, workforce integration, and economic indicators across countries.

Data

ai_data <- tibble(
  country = c("USA","China","India","Germany","UK","Canada","Japan","France"),
  ai_adoption = c(85,90,72,68,75,70,78,66),
  investment = c(500,650,220,180,200,160,240,150),
  gdp_growth = c(2.8,5.4,6.1,1.9,2.1,2.5,1.8,1.7),
  automation = c(70,82,58,61,65,60,69,55),
  workforce_ai = c(40,52,35,30,33,31,38,28)
)

ai_data
## # A tibble: 8 × 6
##   country ai_adoption investment gdp_growth automation workforce_ai
##   <chr>         <dbl>      <dbl>      <dbl>      <dbl>        <dbl>
## 1 USA              85        500        2.8         70           40
## 2 China            90        650        5.4         82           52
## 3 India            72        220        6.1         58           35
## 4 Germany          68        180        1.9         61           30
## 5 UK               75        200        2.1         65           33
## 6 Canada           70        160        2.5         60           31
## 7 Japan            78        240        1.8         69           38
## 8 France           66        150        1.7         55           28

Figure 1: AI Adoption by Country

ggplot(ai_data,
       aes(x = reorder(country, ai_adoption),
           y = ai_adoption,
           fill = country)) +
  geom_col() +
  coord_flip() +
  labs(
    title = "AI Adoption Rate by Country",
    x = "Country",
    y = "AI Adoption (%)"
  ) +
  theme_minimal()

Figure 2: AI Investment by Country

ggplot(ai_data,
       aes(x = country,
           y = investment,
           fill = country)) +
  geom_col() +
  labs(
    title = "AI Investment by Country",
    x = "Country",
    y = "Investment (Billions USD)"
  ) +
  theme_minimal()

Figure 3: AI Investment vs GDP Growth

ggplot(ai_data,
       aes(x = investment,
           y = gdp_growth,
           color = country,
           size = ai_adoption)) +
  geom_point() +
  labs(
    title = "AI Investment and GDP Growth",
    x = "Investment (Billions USD)",
    y = "GDP Growth (%)"
  ) +
  theme_minimal()

Figure 4: Automation Levels

ggplot(ai_data,
       aes(x = reorder(country, automation),
           y = automation,
           fill = automation)) +
  geom_col() +
  coord_flip() +
  scale_fill_viridis_c() +
  labs(
    title = "Automation Levels by Country",
    x = "Country",
    y = "Automation (%)"
  ) +
  theme_minimal()

Figure 5: Workforce AI Integration

ggplot(ai_data,
       aes(x = country,
           y = workforce_ai,
           fill = country)) +
  geom_bar(stat = "identity") +
  labs(
    title = "Workforce AI Integration",
    x = "Country",
    y = "Workforce Using AI (%)"
  ) +
  theme_minimal()

Figure 6: Distribution of AI Adoption

ggplot(ai_data,
       aes(x = ai_adoption)) +
  geom_density(fill = "lightblue", alpha = 0.6) +
  labs(
    title = "Distribution of AI Adoption Rates",
    x = "AI Adoption Rate",
    y = "Density"
  ) +
  theme_minimal()

Figure 7: Heatmap of AI Metrics

heat_data <- ai_data %>%
  select(country, ai_adoption, automation, workforce_ai) %>%
  pivot_longer(-country)

ggplot(heat_data,
       aes(x = name,
           y = country,
           fill = value)) +
  geom_tile() +
  scale_fill_viridis_c() +
  labs(
    title = "Heatmap of AI Metrics",
    x = "Metric",
    y = "Country"
  ) +
  theme_minimal()

Figure 8: Interactive Plotly Visualization

plot_ly(
  ai_data,
  x = ~investment,
  y = ~ai_adoption,
  color = ~country,
  size = ~automation,
  type = "scatter",
  mode = "markers",
  text = ~paste(
    "Country:", country,
    "<br>Investment:", investment,
    "<br>AI Adoption:", ai_adoption
  )
) %>%
  layout(
    title = "Interactive AI Adoption and Investment Analysis",
    xaxis = list(title = "Investment (Billions USD)"),
    yaxis = list(title = "AI Adoption Rate (%)")
  )

Conclusion

The visualizations indicate that countries with higher AI investment generally show stronger AI adoption and workforce integration. Interactive exploration helps reveal patterns between investment, automation, and economic performance.