Tech giants like Microsoft and Google are now relying heavily on generative AI tools to produce significant portions of their programming code, marking a shift that could reshape the software development landscape entirely.

Tech Giants Lean on AI to Write Code

During a recent chat at Meta’s LlamaCon conference, Microsoft CEO Satya Nadella revealed that up to 30% of code within Microsoft’s repositories is now being written by AI systems. While the percentage varies depending on the programming language, with AI showing stronger results in Python than in more complex languages like C++, the shift is undeniable.

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This trend isn’t unique to Microsoft. Just days earlier, Alphabet CEO Sundar Pichai disclosed that more than 30% of Google’s new code is now AI-generated, up from 25% just six months ago. Pichai said the technology is deeply integrated across teams, helping not only developers but also non-technical departments like finance and customer service to operate more efficiently.

“We’re still in the early days, but the initial use cases have been transformative,” Pichai said during Alphabet’s Q1 earnings conference. He emphasized that the company is working on more advanced “agentic workflows” to further deepen AI’s role in software development.

Meanwhile, Microsoft CTO Kevin Scott has gone a step further, projecting that by 2030, up to 95% of code could be AI-generated. But he was quick to clarify that this won’t replace software engineers. Instead, it signals a shift in how developers work. According to Scott, the future of coding will be about guiding AI systems through natural language prompts rather than manually writing every line of code.

“This doesn’t mean AI is doing all the software engineering,” Scott said. “It means developers will become masters of prompting – defining what they want, while the AI handles the heavy lifting.”

Other industry leaders, including IBM’s CEO, have echoed similar sentiments. While acknowledging that AI can handle up to 30% of repetitive coding tasks, they point out its current limitations in tackling more complex problems.

As companies race to stay ahead in the AI arms race, developers are hoping that the future of coding will be a collaboration between human creativity and machine efficiency.