Investors are pricing in a 32.6% AI productivity boost for software engineers

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Investors appear to be betting that AI will deliver substantial gains in software engineering productivity, according to economists who used stock market movements to estimate the technology's expected impact.

Economists affiliated with the University of California, Berkeley (UCB) and the London School of Economics and Political Science (LSE) say that between November 2022 and December 2025, "AI increased the market's expected present value of software engineering productivity by the equivalent of a permanent 32.6 percent productivity increase."

Alex Blumenfeld (UCB), Jonathon Hazell (LSE), Chen Lian (UCB), and Andreas Schaab (UCB) describe their findings in a National Bureau of Economics Research paper titled "The Macroeconomic Effect of AI: Sizing the Software Engineering Channel."

The authors argue that investors have increasingly priced anticipated gains from AI development tools into company valuations since the introduction of ChatGPT in November 2022.

"We empirically measure whether firms with larger software engineering payroll shares experience larger stock-price increases when the AI stock index rises," explained 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.

"A preliminary look at our data suggests that total software engineering employment among the firms covered has increased over the past few years. But our productivity estimate does not depend on that employment trend at all."

Rather than measuring developers' output directly, the researchers examined how company stock returns respond to news AI and whether that response varies with the proportion of each company's payroll devoted to software engineering.

"By 'news AI,' we mean new information reflected in stock prices," explained Lian. "As discussed above, we combine empirical measurements with an economic model to infer how AI has changed investors' expectations of software engineering productivity and the implied GDP impact."

Lian acknowledges that market expectations may not fully materialize. "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."

The market-implied productivity gain of 32.6 percent is comparable in magnitude to the 21-56 percent acceleration on individual tasks reported by other researchers, the authors say. They note however that task-level gains can be offset by bottlenecks that limit productivity gains. In the context of software development that might take the form of code reviews that can't keep pace with surging commit figures.

Feeding the estimated productivity gain into their economic model also produces a sizeable implied effect on GDP.

"News AI from November 2022 to December 2025 corresponds to a present-value GDP increase equivalent to a permanent 3.61 percent level increase," the authors report.

As to whether the productivity gains seen in software engineering are extensible to other industry sectors, Lian said: "Our methods can be used to study the economic impact of AI through other channels, which we plan to explore in follow-up work." ®

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