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AI could boost software engineer productivity by 32.6%

Tools such as Anthropic Claude Code or OpenAI Codex have changed the face of software development, and all the signs are that this investment is set to increase further.

AI could boost software engineer productivity by 32.6%

Tools such as Anthropic Claude Code or OpenAI Codex have changed the face of software development, and all the signs are that this investment is set to increase further. But is paying a monthly subscription (and perhaps additional usage fees) cost-effective?

What changed

But is paying a monthly subscription (and perhaps additional usage fees) cost-effective? Will the increasing level of investment in AI-generated software prove to be worthwhile? This is still a developing thread, so the useful part is knowing which source signals are hardening and which ones still need caution. In software, the upgrades worth caring about are the ones that make workflows cleaner, reduce mistakes, and remove the need for extra tools.

Price and bundle value

That’s a question several economists from the US National Bureau of Economic Research have attempted to answser, at least indirectly. Their paper, snappily entitled The Macroeconomic Effect Of AI: Sizing The Software Engineering Channel , attempts to calculate how much AI has increased the productivity of software engineers in enterprises outside the software and semiconductor industries by looking at their share prices.

AI features that change the value

And the answer? “From November 2022 to December 2025, AI increased the market’s expected present value of software engineering productivity by the equivalent of a permanent 32. 6% productivity increase. The people who feel the value first are often operators, editors, creators, and teams stitching multiple apps into one daily workflow. The next step is to see whether the current signals harden into a durable change or fade as a short-lived experiment.

Who should pay attention

That’s not to say that your software engineers will be that much more productive, but it’s a starting point for allocating budget between AI tool use and payroll. The next step is to see whether the current signals harden into a durable change or fade as a short-lived experiment. That is why the useful reading move is not to stop at the headline, but to compare the promise, the workflow change, and the likely cost before deciding anything.

Patrick Tech Media take

Patrick Tech Media reads this kind of move as a real utility race: the package that removes steps, bundles tools, and lowers hidden cost usually wins longer than the launch buzz. Patrick Tech Media will keep checking Computerworld to see whether the value holds once the rollout broadens. That is why the useful reading move is not to stop at the headline, but to compare the promise, the workflow change, and the likely cost before deciding anything.

Source notes

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