- A survey by OutSystems and KPMG reveals that 84% of IT leaders have incorporated AI into their development processes recently.
- AI and automation have led to up to a 50% reduction in development time for 75% of software executives.
- AI is also expanding into areas like UI design, code generation, and maintenance, driving a shift towards faster, more efficient development.
A new survey by OutSystems and KPMG reveals that as artificial intelligence (AI) expands, IT leaders are diving into new AI applications in software development. The study of 555 software executives shows that 84% have begun using AI in their development processes over the past six months to five years, with IT services leading the charge. While EMEA and North America show similar adoption rates, APAC is rapidly catching up.
According to the official press release provided to Newzchain, the survey also reveals that AI is primarily used in testing, quality assurance, and security vulnerability detection within software development. However, generative AI is poised to revolutionize these areas by boosting efficiency and adding new capabilities. In fact, 75% of software executives report up to a 50% reduction in development time thanks to AI and automation.
“AI is redefining the impossible,” said Paulo Rosado, CEO and founder at OutSystems.
“I’m laser-focused on helping teams compress multi-year legacy modernization projects into just a few months. The latest AI disruptions have brought us the potential to compress these development timelines into even shorter and faster projects. With AI, historically impossible transformation projects are not only possible but easier, cheaper, and faster to accomplish.”
Furthermore, early adopters are expanding AI use into UI design, code generation, DevOps, and maintenance. Nearly all plan to increase investment in AI-driven SDLC management within the next two years, with 71% incorporating AI into their development workflows, highlighting AI's growing role in innovation and competitiveness.
“Right now, the developer’s role is shifting from code writer to code reviewer,” said Rodrigo Coutinho, Co-founder and AI Project Manager at OutSystems.
“Large language models (LLMs) are a big help, but they still make mistakes. But as these models evolve, and trust in the resulting code improves, the developer’s role will be more akin to that of an orchestrator and acceptance tester of AI-generated outputs.”
Despite AI being a nascent technology just a few years ago, the report shows growing confidence in its capabilities—half of respondents said AI has improved software quality, decision-making, and efficiency in testing and quality assurance.
However, this confidence comes with awareness of risks like tech debt from orphan code, AI hallucinations, lack of context for specific coding needs, and scalability issues. With AI integrated into SDLC processes, 56% of respondents reported or anticipated higher-quality applications, fewer bugs, and better performance.
Edited by Harshajit Sarmah
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