Over a quarter (25%) of Google’s internal source code is AI-generated, according to CEO Sundar Pichai, hinting at what's in store for the future of development at big tech firms.
Speaking during a recent earnings call, Pichai explained that the firm is using AI within its development teams to improve coding processes, as well as to boost productivity and efficiency.
The code in question is subject to human approval, Pichai added, as engineers are kept in the loop to review and accept AI-generated code. This helps improve engineer workflows and allows them to move faster, he said.
Google’s AI source code forms part of its full-stack approach to the technology, which Pichai noted also involves rolling out its Gemini models more widely to developers and focusing on tools such as GitHub Copilot.
Google’s announcement is a sign of things to come, according to Camden Woollven, Group Head of AI Product Marketing at GRC International Group, though it might take time for the entire industry to catch up.
“Google's got advantages other companies don't, such as massive code repositories, cutting-edge AI tools, and the resources to implement this safely,” Woollven told ITPro.
“Most companies won't hit 25% anytime soon, but they're definitely heading in that direction.”
It’s also important to put the headline statistic in context, Woollven said. While 25% of Google’s code is AI-generated, this doesn’t mean AI is writing full systems from scratch - rather, it’s complementing human development.
AI coding tool uptick
News of Google’s sizable AI code portfolio comes as research increasingly points to the growing popularity of AI coding tools.
According to a GitHub report that surveyed 2,000 software engineers and developers, 97% said that they had used AI coding tools at work at some point. Many of the surveyed developers also reported better code quality and faster language adoption.
A similar survey from Black Duck Software found that nine-in-ten developers reported using AI coding tools, with some of the most enthusiastic adopters working in technology and cybersecurity.
This uptick could have major implications for application development, according to Manoj Chaudhary, CTO of Jitterbit.
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"Traditionally, building applications required dedicated developers, creating a bottleneck for businesses with limited resources. This meant a long tail of unmet needs, with countless applications left unbuilt due to the dependence on centralized IT teams,” Chaudhary told ITPro.
“AI is now breaking down these barriers. AI-powered tools are lowering the barriers to entry, allowing anyone with a basic understanding of what’s needed to automate tasks and processes,” he added.
Chaudhary argued that AI coding tools can democratize automation and create more agile, more productive environments.
Question marks over AI code
Despite the apparent surge in AI code generation, the industry is not without its concerns. Reports show that many developers question the quality of AI-generated code and its maintainability.
According to a report from Google itself, 39% of surveyed developers do not trust and lack confidence in AI-generated code, despite three-quarters (75%) using AI for at least one daily responsibility.
Other research from GitClear, for example, found concerning trends around maintainability in 153 million lines of examined code, predicting that ‘code churn’ - code that must be changed after its completion - could double in 2024.
Black Duck’s research also pointed toward growing developer worries in this regard, with two-thirds of respondents noting they’re increasingly concerned about the security and safety of AI-generated code.
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