| As generative AI becomes increasingly integrated into the software development lifecycle, the once-booming software job market is showing signs of cooling. Empirical data indicate that, alongside industrywide layoffs, university enrollment in computer science programs has declined in recent years, reversing a two-decade growth trend. The software industry, being knowledge-intensive, digital, highly scalable, and talent-dependent, has unique characteristics that prior research on the economic impact of AI advancement has largely overlooked. This study addresses this gap by leveraging the U.S. software industry data to construct an econometric model examining the effects of AI adoption on software labor markets. Our analysis reveals a significant correlation between the reduction of software development positions and the adoption of AI. Furthermore, by modeling a production function, we provide quantitative evidence of the substitution effect between AI investment and human labor. These findings suggest that generative AI is not merely a productivity tool but a structural disruptor reshaping the "barrier to entry" for the profession. The results provide insights for policymakers, educators, and industry leaders seeking to assess the sustainability of the software talent ecosystem in an AI-augmented era. |
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