Software

Pushing boundaries with AI in software development

“Developers are creatures of habit, and we all have our muscle memory in terms of how we get work done,” Gartner analyst tells IT Brew.
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Amelia Kinsinger

3 min read

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AI’s use cases for software development processes are helping to accelerate the software development industry and pushing boundaries—but Gartner analyst Philip Walsh told IT Brew that human habits are standing in the way.

“Developers are creatures of habit, and we all have our muscle memory in terms of how we get work done,” Walsh said. “You can’t just give someone a new tool and say, ‘Oh, you’re going to be 50% more productive now.’”

Momentum time. Taking existing processes and augmenting them is one of the main ways AI can make things more efficient. AI tools can assist with testing, monitoring, generating code and design, and many other responsibilities.

Research from Gartner predicts increased use of AI in software development. Code assistance in particular is expected to reach high levels, as the firm found in a March 2024 report, “How to Communicate the Value of AI Code Assistants.”

“By 2028, 75% of enterprise software engineers will use AI code assistants, up from less than 10% in early 2023,” the firm wrote. “By 2028, systematic adoption of AI code assistants in 2023 will result in at least 36% compounded developer productivity growth.”

Chris Reddington, GitHub’s senior product manager of strategy for developer relations, wrote in early July that automation can assist developers in learning and streamlining processes—in fact, 92% of developers are using AI coding toolstoday. It’s about more than efficiency—it’s about taking a broad look at what you’re working with, Reddington said.

“AI can help free developers at any level gain a more rounded view of the challenge they are trying to solve and the routes they can take to solve it,” Reddington wrote. “Rather than looking at a generic code sample, AI can provide explanations and examples in the context of their problem, enabling them to learn.”

Coding efficiency is important for DevOps augmentation, SAS Principal Software Development Engineer Billy Dickerson told ZDNet.

“Combining the DevOps and AI domains can be complementary by enhancing all phases of the software development lifecycle and enabling software to ship to market more rapidly, reliably, and efficiently,” Dickerson said.

Moving on up. As with many things AI in 2024, the hype exceeds the reality of what could be expected from the technology. But, Walsh told IT Brew, the promise and value of AI are real, even if the technology has not dramatically reshaped the software development industry.

“There’s definitely still plenty of hype out there; vendors need to sell their products,” Walsh said. “In terms of enterprise end users, we are moving past the peak of inflated expectations, a little bit into the trough of disillusionment—this is not proving to be a dramatic cost reduction mechanism, no one’s firing half their developers because AI is making everyone radically more productive, that simply has not happened.”

Top insights for IT pros

From cybersecurity and big data to cloud computing, IT Brew covers the latest trends shaping business tech in our 4x weekly newsletter, virtual events with industry experts, and digital guides.

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