Gen AI boosts productivity, but only for certain developers – heres why

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ZDNET’s key takeaways

• Close to one-third of code is now AI-generated.
• Developer productivity is up 4% due to generative AI.
• Productivity gains are limited to more experienced developers.

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The amount of AI-generated code worldwide has grown sixfold over the past two years, from 5% in 2022 to nearly 30% by the end of 2024. Along with it has come a measurable increase in programmer productivity.

These are some of the findings from a new studyby the Complexity Science Hub (CSH), which examined the impact of AI tools and platforms on software development. Researchers developed a model that was applied to a large dataset covering software development activity across six countries.

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The cost implications of saving development hours are vast, as US companies alone are estimated to spend more than $600 billion annually on programming-related labor costs, the study’s authors point out.

Productivity gains correlate with experience

Generative AI has increased programmer productivity by close to 4%, they estimate. There’s a fissure in the data, however: less-experienced programmers use AI more frequently (37%), but productivity gains are seen almost exclusively among experienced developers.

Gen AI reshapes both the volume and nature of programming work, according to the CSH research team, led by Simone Daniotti. “Comparing the same developer before and after adopting gen AI, we show that AI adoption substantially increases output. Developers using gen AI are also more likely to incorporate novel combinations of software libraries into their code, suggesting they venture into new technical domains using unfamiliar building blocks.”

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Industry executives celebrate any productivity boosts, but caution that it is just one dimension of a successful move into the AI realm. “When AI is layered onto operations, organizations see a variety of benefits that more closely align ongoing projects and products with business objectives,” said Cameron van Orman, chief marketing and strategy officer and general manager of automotive solutions at Planview.

“The manual work of chasing updates, identifying risks, and normalizing reporting can all be automated,” he continued. “AI can also surface cross-portfolio and value stream dependencies that previously only a handful of highly experienced project managers would see, eliminating visibility gaps caused by systems, data, and tool limitations.”

Don’t neglect structure and accountability

The benefits for developers go beyond speed and productivity. “We conducted a survey among 1,000+ developers and found out that 76% believe AI makes their work more fulfilling, as it allows them to focus on innovation and creative problem-solving,” said Guillermo Carreras, associate vice president of delivery at BairesDev. “Your team can get more meaningful work because routine work is handled. This makes the investment worthwhile; speed is just a side effect.”

In addition, seeking speed and productivity alone misses important elements of the software development process. “Without structure and accountability, even the most promising AI projects will stall, and AI won’t have the impact on the software development lifecycle that it should,” van Orman added. “When scaling from experimentation to enterprise-wide adoption, software leaders must prioritize disciplined planning, prioritization, and follow-through.”

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Then there is the striking lack of productivity seen among early-career developers in the CSH study. Gen AI estimated adoption rates “are higher among early-career developers,” the study shows. “However, both productivity and exploration gains concentrate almost exclusively among senior-level developers. In contrast, although early-career developers used gen AI more, they do not realize the same benefits.”

The reason for this is that it “may reflect differences in how well developers utilize gen AI across a broader set of tasks,” Daniotti and her co-authors theorize. “Senior-level developers will, for instance, be quicker to interpret and spot mistakes in AI-generated code.”

‘Do more with the same’

This, in turn, means greater opportunities for experienced software professionals. “Given how fast markets move and the exponential pace of innovation, I think it will create more demand for software developers to deliver more features per unit time,” said Venky Veeraraghavan, chief product officer at DataRobot. “The calculus will not be ‘do the same with less’ but ‘do more with the same.'”

With AI tools handling coding faster, “developers can think about architecture and edge cases that actually require judgment,” said Carreras. “It also facilitates the documentation process and test cases generation.”

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Developers who thrive “will be the ones who treat AI like a junior engineer on the team: helpful, fast, but in need of oversight,” said Eric Cheng, co-founder and CEO at Jobright. “Knowing how to prompt, review, and improve AI output will be as essential as writing clean code.”

Gen AI increased experimentation with new libraries, according to the CSH study. “This suggests gen AI allowed users to advance faster to new areas of programming, embedding new types of functionality in their code,” the report states. “Gen AI increases individual innovation, pushing individuals’ capabilities in terms of the use of new combinations of libraries. However, again, only experienced, senior-level users seem able to leverage gen AI in this way, with important consequences for career development and learning in the presence of gen AI.”