The Global AI Skills Divide: Who Is Benefiting From the AI Boom?

The Global AI Skills Divide: Who Is Benefiting From the AI Boom?

AI is often discussed as a future threat, but job market data shows the shift has already started. Employers are increasingly asking for AI-related skills, yet this demand is not rising equally across countries. This creates an emerging AI skills divide: workers in some countries may gain earlier access to new high-skill opportunities, while others may be left behind as labour markets change.

Why Should Readers Care?

Artificial Intelligence is expected to influence almost every industry, from healthcare and education to finance and manufacturing. While much public discussion focuses on whether AI will replace jobs, a more immediate question is whether workers possess the skills employers are already demanding. Understanding where AI-related job demand is growing can help students, graduates, and policymakers prepare for future workforce changes.

library(tidyverse)
library(plotly)
library(DT)
library(scales)

url <- "https://ourworldindata.org/grapher/share-artificial-intelligence-job-postings.csv"

ai <- read_csv(url)

names(ai)[4] <- "ai_job_share"

countries <- c(
  "Australia",
  "United States",
  "United Kingdom",
  "Canada",
  "Germany",
  "France",
  "India",
  "Japan"
)

ai_focus <- ai %>%
  filter(Entity %in% countries)

Chart 1: Growth of AI-related jobs

p1 <- ggplot(
  ai_focus,
  aes(
    x = Year,
    y = ai_job_share,
    colour = Entity,
    group = Entity,
    text = paste(
      "Country:", Entity,
      "<br>Year:", Year,
      "<br>AI Job Share:", round(ai_job_share,2), "%"
    )
  )
) +
  geom_line(linewidth = 1.2) +
  geom_point(size = 2) +
  labs(
   title = "Australia Is Growing, But Global Competition Is Intensifying",
    subtitle = "Growth of AI-related job postings over time",
    x = "Year",
    y = "Share of AI-related Job Postings (%)",
    colour = "Country"
  ) +
  theme_minimal(base_size = 14) +
theme(
  plot.title = element_text(face = "bold")
)

ggplotly(p1, tooltip = "text")

The first visualisation shows the share of job advertisements requiring AI-related skills over time. Across most countries, demand for AI skills has increased significantly since 2014. This suggests that AI is becoming increasingly important across a wide range of industries.

Chart 2: Current AI Job Demand Ranking

latest_year <- max(ai$Year, na.rm = TRUE)

latest <- ai %>%
  filter(Year == latest_year) %>%
  arrange(desc(ai_job_share)) %>%
  slice_head(n = 15)

p2 <- ggplot(
  latest,
  aes(
    x = reorder(Entity, ai_job_share),
    y = ai_job_share,
    text = paste(
      "Country:", Entity,
      "<br>Year:", Year,
      "<br>AI Job Share:", round(ai_job_share, 2), "%"
    )
  )
) +
  geom_col() +
  coord_flip() +
  labs(
    title = paste("Countries With the Highest AI-related Job Posting Share in", latest_year),
    x = "",
    y = "Share of AI-related Job Postings (%)"
  ) +
  theme_minimal(base_size = 14) +
theme(
  plot.title = element_text(face = "bold")
)

ggplotly(p2, tooltip = "text")

This visualisation ranks countries according to the latest share of AI-related job postings. The results highlight which economies are currently leading demand for AI talent.

Chart 3: Australia Compared With Similar Countries

comparison <- c("Australia", "United States", "United Kingdom", "Canada")

p3 <- ai %>%
  filter(Entity %in% comparison) %>%
  ggplot(
    aes(
      x = Year,
      y = ai_job_share,
      colour = Entity,
      group = Entity,
      text = paste(
        "Country:", Entity,
        "<br>Year:", Year,
        "<br>AI Job Share:", round(ai_job_share, 2), "%"
      )
    )
  ) +
  geom_line(linewidth = 1.2) +
  geom_point(size = 2) +
  labs(
    title = "Australia Is Competing in a Global AI Labour Market",
    subtitle = "Comparison with similar English-speaking economies",
    x = "Year",
    y = "Share of AI-related Job Postings (%)",
    colour = "Country"
  ) +
  theme_minimal(base_size = 14) +
theme(
  plot.title = element_text(face = "bold")
)

ggplotly(p3, tooltip = "text")

Australia is compared with the United States, Canada and the United Kingdom. This comparison helps evaluate whether Australia is keeping pace with other advanced economies in AI workforce development.

Chart 4: Which Countries Experienced the Largest Growth?

change <- ai %>%
  filter(Year %in% c(min(Year), max(Year))) %>%
  select(Entity, Year, ai_job_share) %>%
  pivot_wider(names_from = Year, values_from = ai_job_share) %>%
  drop_na()

names(change)[2:3] <- c("Start", "Latest")

change <- change %>%
  mutate(Growth = Latest - Start) %>%
  arrange(desc(Growth)) %>%
  slice_head(n = 15)

p4 <- ggplot(
  change,
  aes(
    x = reorder(Entity, Growth),
    y = Growth,
    fill = Growth,
    text = paste(
      "Country:", Entity,
      "<br>Growth:", round(Growth, 2), "%"
    )
  )
) +
  geom_col() +
  coord_flip() +
  labs(
    title = "Growth in AI-related Job Demand Since 2014",
    x = "",
    y = "Increase in AI Job Posting Share (%)"
  ) +
  theme_minimal(base_size = 14) +
theme(
  plot.title = element_text(face = "bold")
)

ggplotly(p4, tooltip = "text")

Growth rates provide a different perspective from current rankings. Several countries have experienced rapid increases in AI-related hiring despite not being current leaders.

Chart 5: AI Job Demand Across Countries and Time

heat_data <- ai %>%
  filter(Entity %in% countries)

p5 <- ggplot(
  heat_data,
  aes(
    x = Year,
    y = Entity,
    fill = ai_job_share,
    text = paste(
      "Country:", Entity,
      "<br>Year:", Year,
      "<br>AI Job Share:", round(ai_job_share, 2), "%"
    )
  )
) +
  geom_tile() +
  labs(
    title = "AI Job Demand Across Countries and Years",
    x = "Year",
    y = "Country",
    fill = "AI Job Share (%)"
  ) +
  theme_minimal(base_size = 14) +
theme(
  plot.title = element_text(face = "bold")
)

ggplotly(p5, tooltip = "text")

The heatmap reveals a growing divide between countries that are rapidly integrating AI into their economies and those where AI-related opportunities remain relatively limited.

Data Table

datatable(
  ai_focus,
  options = list(
    pageLength = 10,
    scrollX = TRUE
  ),
  caption = "Interactive table of AI-related job postings"
)

Conclusion

The findings show that AI is already reshaping labour markets worldwide. While demand for AI-related skills is increasing across many countries, the pace of growth varies considerably. The results highlight the importance of AI education and workforce readiness in an increasingly technology-driven economy. # References

Our World in Data. (2026). Share of artificial intelligence jobs among all job postings. https://ourworldindata.org/grapher/share-artificial-intelligence-job-postings

Stanford University. (2026). AI Index Report 2026.