Economic Research Suggests AI Tools Could Drive Significant Gains in Developer Productivity
Economists from the US National Bureau of Economic Research analyzed stock price movements to estimate how much AI has improved software engineering productivity, finding an expected 32.6% increase in productivity gains from November 2022 through December 2025. The researchers used a mathematical model tracking how companies with larger engineering teams saw greater stock price appreciation when AI-related news emerged, indicating market confidence in productivity improvements. The figure serves as a benchmark for enterprises considering investment in AI-assisted development tools.
Researchers at the National Bureau of Economic Research employed an innovative methodology to assess AI's effect on software development productivity. Rather than surveying companies directly, they analyzed stock market reactions to AI-related announcements, focusing on how firms with larger engineering workforces experienced different share price movements than those with smaller technical teams. This approach allowed them to infer what financial markets expected regarding productivity improvements from AI adoption.
The 32.6% figure represents the market's collective forecast for productivity gains across a three-year window beginning in late 2022, when generative AI tools became widely available to developers. The researchers acknowledge this projection may not reflect actual realized productivity, but rather serves as a data point for enterprise decision-makers evaluating whether investing in AI-assisted coding platforms justifies the subscription and operational costs involved.
This research could influence enterprise technology spending decisions by providing a quantified benchmark for expected returns on AI tool investments. Companies with significant engineering teams may feel encouraged to adopt AI-assisted development platforms based on market confidence in productivity gains. However, actual results will depend on implementation effectiveness and workforce adaptation, meaning some organizations may experience outcomes differing from the market's collective expectations reflected in stock valuations.