Chart 1: AI Adoption is Accelerating

AI has been accelerating with its spread and its reshaping how organisations operate. Since 2022, GenAI has been surging and the huge question is which field will AI change the most?

Chart 2: Not Everyone Has Equal Access

Not everyone has access to the education that is required for GenAI Many rural schools don’t offer computer science classes with proper GenAI education which can create a gap for students before they even enter the workforce.

Chart 3: The Gender Gap in CS Education

However the access gap is not the only issue, there is also a significant gender gap in CS education from associate to PhD degrees. If AI is truly our future then half of the population is being left behind.

Chart 4: AI is Reshaping Every Business Function

This means for jobs in the business sector AI will increase rather than decrease whereas software engineering is a different story. The gap between the increase and decrease is way smaller and is concerning as software engineering is the most popular career path for newer Computer Science graduates.

Chart 5: Computer Science Graduates Are Growing — But Is It Enough?

Computer science graduates are rising especially with more completing Masters degrees. The looming question is will this be enough to fill the demand for AI related jobs in the future and are we producing them to meet the demands of the future AI-driven economy?

Acknowledgment:

Claude (Anthropic) has been used but only as a guide with caption and annotation errors. All final code and ideas are my own and places where Claude was used have been thoroughly checked before being implemented

References:

Maslej, N., Fattorini, L., Bryson, M., Okun, O., Bengio, Y., Shoham, Y., & Perrault, R. (2025). Artificial Intelligence Index Report 2025. Stanford Institute for Human-Centered Artificial Intelligence. https://hai.stanford.edu/ai-index/2025-ai-index-report

Anthropic. (2025). Claude (claude-sonnet-4-6) [Large language model]. https://www.anthropic.com

Sievert, C. (2020). Interactive web-based data visualization with R, plotly, and shiny. Chapman and Hall/CRC. https://plotly-r.com

Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T. L., Miller, E., Bache, S. M., Müller, K., Ooms, J., Robinson, D., Seidel, D. P., Spinu, V., … Yutani, H. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686