The researchers—Alex Blumenfeld (UC Berkeley), Jonathon Hazell (LSE), Chen Lian (UC Berkeley), and Andreas Schaab (UC Berkeley)—analysed how company stock returns responded to AI-related news between November 2022 and December 2025. They found that firms with larger software engineering payroll shares experienced greater stock price increases when the AI stock index rose, which they attribute to investor expectations of productivity gains.
“We empirically measure whether firms with larger software engineering payroll shares experience larger stock-price increases when the AI stock index rises,” said Chen Lian, assistant professor of finance at UC Berkeley, in an email to The Register. “We then use an economic model to translate that relationship into the AI-driven software engineering productivity gains investors anticipate.”
The implied 32.6% productivity boost is comparable to the 21–56% acceleration on individual tasks reported by other studies. However, the authors note that task-level gains can be offset by bottlenecks such as code reviews unable to keep up with surging commit volumes.
Lian acknowledged that market expectations may not fully materialise. “Our estimates capture the market’s assessment of current and future productivity gains, and markets can be overly optimistic or pessimistic,” he said. “The advantage is a forward-looking measure, available in real time, when many of AI’s effects have yet to play out.”
Feeding the estimate into their economic model also produces a present-value GDP increase equivalent to a permanent 3.61% level rise. Lian said the method can be extended to study AI’s impact through other channels in future work.