Google’s State of DevOps Report for 2024 revealed how quickly artificial intelligence is being integrated into our lives in the software industry. According to the report, a survey of more than 3,000 developers and IT professionals around the world showed that 76% of them actively use AI tools in their daily tasks such as writing code, summarizing information and explaining code.

Google’s report reveals that 76% of developers are now writing code with the help of AI

AI-powered software development is now a routine for many professionals. So why has it been adopted so quickly? According to the report, these tools provide developers with a more efficient working environment, lighten their daily workload and speed up the coding process.

The research, conducted by Google Cloud, revealed not only the interest of individual developers in AI, but also the investment of companies in the field. 81% of respondents said that the companies they work for are investing significantly in AI technologies, and with these investments, they are directing their technical resources to AI-based projects.

In particular, AI’s productivity gains are quite remarkable. The report reveals that the use of AI-powered tools improves code quality by 3.4% and the quality of written documents by 7.5%. It is also emphasized that code review processes accelerated and approval processes accelerated by 1.3%. In other words, AI improves quality at every stage of workflows.

However, not everything is rosy. There are some unexpected consequences of AI-assisted software development. The report states that despite the productivity gains that AI provides, software delivery performance dropped by 1.5% and delivery stability declined by 7.2%.

This means that while AI makes developers’ lives easier, it can also pose some challenges in terms of speed and consistency in software deliveries. Among the reasons behind this are factors such as the fact that AI-enhanced code requires more testing and editing.

Still, these challenges have not deterred many companies from using AI. On the contrary, many companies are focusing on AI technologies to create a more efficient software development process with customized language models and internal data.

Investments in small language models, in particular, allow them to increase efficiency without the need for massive data processing power. So, while AI is transforming software development, learning to work with it and using it correctly is just as important as developing the technology.