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- A new Google study suggests AI adoption in software development has surged to 90%.
- Google’s senior director of product says AI means more people will be involved in deploying products.
- He said that knowing programming languages remains critical.
There’s no more hiding from AI if you’re a software engineer.
Google Cloud released a report on Tuesday about AI-assisted software development. The study, from the tech giant’s DevOps Research and Assessment team, shows that AI adoption has surged to 90% among software professionals. That’s a 14% increase from last year.
The findings are based on a survey of 5,000 global technology professionals and more than 100 hours of qualitative interviews. Developers and other professionals are spending a median of two hours daily using AI in their core workflows, according to the survey.
Nathen Harvey, who leads the DevOps Research and Assessment team, told Business Insider that the findings indicate that using AI in the workplace is nearly universal.
“It’s almost to the point where we could have asked these technologists, ‘Are you using a computer at work?”‘ said Harvey, a developer advocate at Google Cloud.
How software engineer jobs are changing
With AI increasingly being used on the job to generate and review code, write documentation, create test cases, and analyze data, the role of a software engineer is already changing, Google’s Ryan J. Salva said.
Salva, senior director of product management, told Business Insider he expects the “number of builders and creators to dramatically expand,” meaning that more software engineers will also build products rather than just write code.
For example, specification writing, which defines how a product or feature should operate, used to be a large part of a product manager’s job. Salva said that it’s still an important aspect of the job, but product managers can now use AI to go a step further and build prototypes themselves quickly for demoing and testing.
“I expect a lot more people not just to participate in software development, but to get closer to the actual deployment of the software itself,” Salva said.
Google CEO Sundar Pichai said in a June podcast with Lex Fridman that the tech giant has accomplished a 10% engineering velocity increase using AI. Pichai also shared plans to hire more engineers next year, though he didn’t specify how many.
“We plan to hire more engineers next year because the opportunity space of what we can do is expanding,” Pichai said.
As these tools become more widespread, Salva said that the skills software engineers need are becoming “slightly different.” He said software engineers are spending less time working on writing actual code, and more of their days doing bigger-picture thinking about a product’s architecture or what problems need to be solved.
Salva said he’s observed that software engineers are already thinking differently about their work. “They’re spending a lot more time thinking about ‘what is the product that I’m trying to deliver — the capability that I’m trying to deliver to others?'” Salva said.
Salva said that by integrating AI in the role, the barrier of coding languages like Java or Python has been removed, and more people are able to participate in the full cycle of software development.
“The end product was never just code,” Salva said.
Programming basics remain a priority
While AI can help developers with various tasks, fluency in programming languages is still critical to the job, Harvey said.
Harvey told Business Insider that one of the most surprising insights from the study was that programming syntax memorization, which which means knowing the rules of coding languages, increased in perceived importance for the engineers surveyed. The finding is unexpected because it’s also one of the development-related skills likely to be viewed as outdated in the age of AI, the report said.
Despite widespread AI adoption and its perceived benefits, the report showed that 30% of respondents trusted AI “a little” or “not at all.” Harvey said that with product owners able to create prototypes at a faster rate, they need to make sure that the product works well when it arrives.
“You are going to be entirely unsuccessful if you cannot read the language, at the very least,” Salva said. “There are dozens, if not hundreds, of programming languages out there. One needs to be able to read the book.”
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